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  • Keras Seq2Seq示例 任务很简单,将数字转为中文大写金额,例如 11288 -> 壹万壹仟零捌拾捌元整 我们将尝试利用seq2seq来解决...找到一个将数字中文的python代码 http://blog.csdn.net/zzcwing/article/de...

    Keras Seq2Seq示例

    • 任务很简单,将数字转为中文大写金额,例如 11288 -> 壹万壹仟零捌拾捌元整
    • 我们将尝试利用seq2seq来解决这一问题,整个示例包括以下部分:
      • 建立数据集
      • 设计seq2seq模型
      • 对比不同seq2seq模型

    建立数据集

    • 找到一个将数字转中文的python代码 http://blog.csdn.net/zzcwing/article/details/8763212 我们利用这个来建立数据集
    • 为了让事情变得简单一点,我们对数据集做一些约束:
      • 数据集中的数字大小不超过 10w,也就是说范围在[0, 99999]
      • 都是整数
    • 完整代码在这里
    import random
    import numpy as np
    
    from keras import layers
    from keras.layers import Input, Embedding, Bidirectional, Dense, Concatenate, LSTM
    from keras.models import Model, load_model
    from keras import callbacks
    
    import matplotlib.pyplot as plt
    %matplotlib inline

    以下是数字转中文大写的代码,感谢作者

    # -*- coding: utf-8 -*-
    """
    Created on Sat Apr 06 00:28:24 2013
    
    @author: zzcwing
    """
    #算法说明:要求字符串输入,现将字符串差费为整数部分和小数部分生成list[整数部分,小数部分]
    #将整数部分拆分为:[亿,万,仟]三组字符串组成的List:['0000','0000','0000'](根据实际输入生成阶梯List)
    #例如:600190000010.70整数部分拆分为:['600','1900','0010']
    #然后对list中每个字符串分组进行大写化再合并
    #最后处理小数部分的大写化
    
    class cnumber:
        cdict={}
        gdict={}
        xdict={}
        def __init__(self):
            self.cdict={1:u'',2:u'拾',3:u'佰',4:u'仟'}
            self.xdict={1:u'元',2:u'万',3:u'亿',4:u'兆'} #数字标识符
            self.gdict={0:u'零',1:u'壹',2:u'贰',3:u'叁',4:u'肆',5:u'伍',6:u'陆',7:u'柒',8:u'捌',9:u'玖'}       
    
        def csplit(self,cdata): #拆分函数,将整数字符串拆分成[亿,万,仟]的list
            g=len(cdata)%4
            csdata=[]
            lx=len(cdata)-1
            if g>0:
                csdata.append(cdata[0:g])
            k=g
            while k<=lx:
                csdata.append(cdata[k:k+4])
                k+=4
            return csdata
    
        def cschange(self,cki): #对[亿,万,仟]的list中每个字符串分组进行大写化再合并
    
            lenki=len(cki)
            i=0
            lk=lenki
            chk=u''
            for i in range(lenki):
                if int(cki[i])==0:
                    if i<lenki-1:
                        if int(cki[i+1])!=0:
                            chk=chk+self.gdict[int(cki[i])]                    
                else:
                    chk=chk+self.gdict[int(cki[i])]+self.cdict[lk]
                lk-=1
            return chk
    
        def cwchange(self,data):
            if not '.' in data:
                data = data + '.00'
            cdata=str(data).split('.')
    
            cki=cdata[0]
            ckj=cdata[1]
            i=0
            chk=u''
            cski=self.csplit(cki) #分解字符数组[亿,万,仟]三组List:['0000','0000','0000']
            ikl=len(cski) #获取拆分后的List长度
            #大写合并
            for i in range(ikl):
                if self.cschange(cski[i])=='': #有可能一个字符串全是0的情况
                    chk=chk+self.cschange(cski[i]) #此时不需要将数字标识符引入
                else:
                    chk=chk+self.cschange(cski[i])+self.xdict[ikl-i] #合并:前字符串大写+当前字符串大写+标识符
            #处理小数部分
            lenkj=len(ckj)
            if lenkj==1: #若小数只有1位
                if int(ckj[0])==0: 
                    chk=chk+u'整'
                else:
                    chk=chk+self.gdict[int(ckj[0])]+u'角整'
            else: #若小数有两位的四种情况
                if int(ckj[0])==0 and int(ckj[1])!=0:
                    chk=chk+u'零'+self.gdict[int(ckj[1])]+u'分'
                elif int(ckj[0])==0 and int(ckj[1])==0:
                    chk=chk+u'整'
                elif int(ckj[0])!=0 and int(ckj[1])!=0:
                    chk=chk+self.gdict[int(ckj[0])]+u'角'+self.gdict[int(ckj[1])]+u'分'
                else:
                    chk=chk+self.gdict[int(ckj[0])]+u'角整'
            return chk

    生成数据,范围在[1, 99999]

    pt=cnumber()
    
    # 生成数据,并写入文件中
    num_range = range(1, 100000)
    data_path = 'dataset.txt'
    with open(data_path, 'w') as f:
        for num in num_range:
            num_str = str(num)
            ch_num = pt.cwchange(num_str)
            f.write(num_str + '\t' + ch_num + '\n')

    向量化数据

    num_samples = 50000
    
    data_path = 'dataset.txt'
    # 读入数据
    with open(data_path, 'r') as f:
        lines = f.read().split('\n')
    
    # 打乱顺序
    random.shuffle(lines)
    # 显示部分数据
    for line in lines[:10]:
        print(line)
    72608   柒万贰仟陆佰零捌元整
    17338   壹万柒仟叁佰叁拾捌元整
    99815   玖万玖仟捌佰壹拾伍元整
    38187   叁万捌仟壹佰捌拾柒元整
    79028   柒万玖仟零贰拾捌元整
    95661   玖万伍仟陆佰陆拾壹元整
    29591   贰万玖仟伍佰玖拾壹元整
    11372   壹万壹仟叁佰柒拾贰元整
    31327   叁万壹仟叁佰贰拾柒元整
    84890   捌万肆仟捌佰玖拾元整
    
    input_texts = [] #输入数据,也就是数字字符串
    target_texts = [] #目标数据,也就是中文大写字符串
    input_characters = set()
    target_characters = set()
    # 分割数据为 input_texts 和 target_texts
    # 且统计一些信息
    for line in lines[: min(num_samples, len(lines)-1)]:
        try:
            input_text, target_text = line.split('\t')
        except ValueError:
            print('Error line:', line)
            input_text = ''
            target_text = ''
    
        # 计算 input_texts 中的 tokens数量
        for char in input_text:
            if char not in input_characters:
                input_characters.add(char)
    
        # 计算 target_texts 中的 tokens数量
        for char in target_text:
            if char not in target_characters:
                target_characters.add(char)
    
        # 用 '始'作为开始字符
        # 用 '终'作为结束字符
        target_text = '始' + target_text + '终'
    
        input_texts.append(input_text)
        target_texts.append(target_text)
    
    
    input_characters = sorted(list(input_characters))
    target_characters = sorted(list(target_characters))
    
    max_encoder_seq_length = max([ len(txt) for txt in input_texts])
    max_decoder_seq_length = max([ len(txt) for txt in target_texts])
    
    print('Nunmber of samples:', len(input_texts))
    print('Max sequence length of input:', max_encoder_seq_length)
    print('Max sequence length of outputs:', max_decoder_seq_length)
    Nunmber of samples: 50000
    Max sequence length of input: 5
    Max sequence length of outputs: 13
    
    # 建立字典,用于字符转数字
    
    # '[pad]'表示填充字符
    input_token_index = dict( [(char, i) for i, char in enumerate(['pad']+input_characters)])
    
    # '始'表示开始字符,'终'表示终止字符,'空'表示填充字符
    special_characters = ['空', '始', '终']
    target_token_index = dict([ (char,i ) for i, char in enumerate(special_characters + target_characters)])
    
    num_encoder_tokens = len(input_token_index)
    num_decoder_tokens = len(target_token_index)
    def characters2index(text, char_index):
        # 将字符串向量化
        return [char_index.get(char) for char in text]
    # 创建向量化的数据
    encoder_input_data = np.zeros((len(input_texts), max_encoder_seq_length), dtype=np.int32)
    decoder_input_data = np.zeros((len(target_texts), max_decoder_seq_length), dtype=np.int32)
    # decoder_target_data 需要 one-hot 编码
    decoder_target_data = np.zeros((len(target_texts), max_decoder_seq_length, num_decoder_tokens), dtype=np.float32)
    
    # 填充数据
    for i, (input_text, target_text) in enumerate(zip(input_texts, target_texts)):
        input_indexs = characters2index(input_text, input_token_index)
        encoder_input_data[i, :len(input_indexs)] = input_indexs
    
        target_indexs = characters2index(target_text, target_token_index)
        decoder_input_data[i, :len(target_indexs)] = target_indexs
    
        # decoder_target_data 做one-hot编码,且偏移一位
        for t, index in enumerate(decoder_input_data[i, 1:]):
            decoder_target_data[i, t, index] = 1.0
        decoder_target_data[i, -1, 0] = 1.0

    设计模型

    # 超参数
    encoder_embedding_dim = 10
    decoder_embedding_dim = 20
    latent_dim = 128
    
    batch_size = 64
    epochs = 20

    单向模型

    • 编码器和解码器都是单向lstm
      • 编码器:encoder_input -> encoder_embedding -> encoder_lstm -> …
      • 解码器:decoder_input -> decoder_embbeding -> decoder_lstm -> decoder_dense -> …
    def build_basic_model():
        rnn = layers.LSTM
        # Encoder
        encoder_inputs = Input(shape=(None,), name='encoder_inputs')
        encoder_embedding = Embedding(num_encoder_tokens, encoder_embedding_dim, name='encoder_embedding')(encoder_inputs)
        encoder_lstm = rnn(latent_dim, return_state=True, return_sequences=True, dropout=0.2, recurrent_dropout=0.5, name='encoder_lstm')
        _, *encoder_states = encoder_lstm(encoder_embedding)
    
        # Decoder
        decoder_inputs = Input(shape=(None,), name='decoder_inputs')
        decoder_embedding = Embedding(num_decoder_tokens, decoder_embedding_dim, name='decoder_embedding')(decoder_inputs)
        decoder_lstm = rnn(latent_dim, return_state=True, return_sequences=True, dropout=0.2, recurrent_dropout=0.5, name='decoder_lstm')
        rnn_outputs, *decoder_states = decoder_lstm(decoder_embedding, initial_state=encoder_states)
        decoder_dense = Dense(num_decoder_tokens, activation='softmax', name='decoder_dense')
        decoder_outputs = decoder_dense(rnn_outputs)
    
        basic_model = Model([encoder_inputs, decoder_inputs], [decoder_outputs])
        basic_model.compile(optimizer='adam', loss='categorical_crossentropy')
        return basic_model

    训练单向模型

    # 回调函数
    callback_list = [callbacks.ModelCheckpoint('basic_model_best.h', save_best_only=True)]
    # 获取模型
    basic_model = build_basic_model()
    # 训练
    basic_model_hist = basic_model.fit([encoder_input_data, decoder_input_data], decoder_target_data,
                    batch_size=batch_size, epochs=epochs,
                    validation_split=0.2, callbacks=callback_list)
    Train on 40000 samples, validate on 10000 samples
    Epoch 1/20
    40000/40000 [==============================] - 49s 1ms/step - loss: 1.2564 - val_loss: 0.7960
    Epoch 2/20
    40000/40000 [==============================] - 43s 1ms/step - loss: 0.7724 - val_loss: 0.6788
    Epoch 3/20
    40000/40000 [==============================] - 47s 1ms/step - loss: 0.5891 - val_loss: 0.3697
    ......
    Epoch 20/20
    40000/40000 [==============================] - 46s 1ms/step - loss: 0.0041 - val_loss: 7.0554e-05
    

    测试单向模型

    # 建立推理模型
    def build_basic_inference_model(model_path):
        model = load_model(model_path)
    
        # encoder
        encoder_inputs = Input(shape=(None,))
        # encoder_embedding
        encoder_embedding = model.get_layer('encoder_embedding')(encoder_inputs)
        # get encoder states
        _, *encoder_states = model.get_layer('encoder_lstm')(encoder_embedding)
        encoder_model = Model(encoder_inputs, encoder_states)
    
        # decoder
        # decoder inputs
        decoder_inputs = Input(shape=(None,))
        # decoder input states 
        decoder_state_h = Input(shape=(latent_dim,))
        decoder_state_c = Input(shape=(latent_dim,))
        decoder_states_inputs = [decoder_state_h, decoder_state_c]
    
        # decoder embedding
        decoder_embedding = model.get_layer('decoder_embedding')(decoder_inputs)
        # get rnn outputs and decoder states
        rnn_outputs, *decoder_states = model.get_layer('decoder_lstm')(decoder_embedding, initial_state=decoder_states_inputs)
        decoder_outputs = model.get_layer('decoder_dense')(rnn_outputs)
        decoder_model = Model([decoder_inputs] + decoder_states_inputs, [decoder_outputs]+decoder_states)
    
        return encoder_model, decoder_model
    reverse_input_char_index = dict([(i, char) for char, i in input_token_index.items()])
    reverse_target_word_index = dict([(i, char) for char, i in target_token_index.items()])
    
    def decode_sequence(input_seq, encoder_model, decoder_model):
        # get encoder states
        states_value = encoder_model.predict(input_seq)
    
        # create a empty sequence
        target_seq = np.zeros((1, 1))
        target_seq[0, 0] = target_token_index['始']
    
        # 进行句子的恢复
        stop_condition = False
        decoded_sentence = ''
    
        while not stop_condition:
            output, *decoder_states = decoder_model.predict([target_seq] + states_value)
    
            sampled_token_index = np.argmax(output[0, -1, :])
            sampled_word = reverse_target_word_index[sampled_token_index]
            decoded_sentence += sampled_word
    
            if sampled_word == '终' or len(decoded_sentence) > max_decoder_seq_length:
                stop_condition = True
    
            # update target_seq
            target_seq = np.zeros((1, 1))
            target_seq[0, 0] = sampled_token_index
    
            # update states
            states_value = decoder_states
    
        return decoded_sentence
    # 建立一些测试用的样本
    test_input_texts = [line.split('\t')[0] for line in lines[-20:]]
    test_input_data = np.zeros((len(test_input_texts), max_encoder_seq_length), np.int32)
    for i, test_text in enumerate(test_input_texts):
        test_indexs = characters2index(test_text, input_token_index)
        test_input_data[i, :len(test_indexs)] = test_indexs
    # 导入模型
    model_path = 'basic_model_best.h'
    inference_encoder_model, inference_decoder_model = build_basic_inference_model(model_path)
    # 测试
    for seq_index in range(len(test_input_texts)):
        # Take one sequence (part of the training set)
        # for trying out decoding.
        input_seq = test_input_data[seq_index: seq_index + 1]
        decoded_sentence = decode_sequence(input_seq, inference_encoder_model, inference_decoder_model)
        print('-')
        print('Input sentence:', test_input_texts[seq_index])
        print('Decoded sentence:', decoded_sentence)
    -
    Input sentence: 59798
    Decoded sentence: 伍万玖仟柒佰玖拾捌元整终
    -
    Input sentence: 28307
    Decoded sentence: 贰万捌仟叁佰零柒元整终
    -
    Input sentence: 49323
    Decoded sentence: 肆万玖仟叁佰贰拾叁元整终
    -
    Input sentence: 24169
    Decoded sentence: 贰万肆仟壹佰陆拾玖元整终
    -
    Input sentence: 95323
    Decoded sentence: 玖万伍仟叁佰贰拾叁元整终
    -
    Input sentence: 50104
    Decoded sentence: 伍万零壹佰零肆元整终
    -
    Input sentence: 34650
    Decoded sentence: 叁万肆仟陆佰伍拾元整终
    -
    Input sentence: 60256
    Decoded sentence: 陆万零贰佰伍拾陆元整终
    -
    Input sentence: 42183
    Decoded sentence: 肆万贰仟壹佰捌拾叁元整终
    -
    Input sentence: 68802
    Decoded sentence: 陆万捌仟捌佰零贰元整终
    -
    Input sentence: 63819
    Decoded sentence: 陆万叁仟捌佰壹拾玖元整终
    -
    Input sentence: 32531
    Decoded sentence: 叁万贰仟伍佰叁拾壹元整终
    -
    Input sentence: 25678
    Decoded sentence: 贰万伍仟陆佰柒拾捌元整终
    -
    Input sentence: 42272
    Decoded sentence: 肆万贰仟贰佰柒拾贰元整终
    -
    Input sentence: 48908
    Decoded sentence: 肆万捌仟玖佰零捌元整终
    -
    Input sentence: 74546
    Decoded sentence: 柒万肆仟伍佰肆拾陆元整终
    -
    Input sentence: 11869
    Decoded sentence: 壹万壹仟捌佰陆拾玖元整终
    -
    Input sentence: 75803
    Decoded sentence: 柒万伍仟捌佰零叁元整终
    -
    Input sentence: 75727
    Decoded sentence: 柒万伍仟柒佰贰拾柒元整终
    -
    Input sentence: 67230
    Decoded sentence: 陆万柒仟贰佰叁拾元整终
    

    双向编码器模型

    • 编码器使用双向的lstm,解码器使用单向的lstm

      • 编码器:encoder_input -> encoder_embedding -> bidi_encoder_lstm -> …
      • 解码器:decoder_input -> decoder_embbeding -> decoder_lstm -> decoder_dense -> …
    • 由于编码器是双向的,其状态包括 forward_h, forward_c, backward_h, backward_c,每个状态的shape=(?, latent_dim),需要将foward 和 backward的状态进行合并,合并成为 state_h, state_c,其shape=(?, latent_dim*2)

    • 因此,解码器为了能够接收编码器的状态,解码器的latent_dim要与state_h, state_c一致,因此解码器的LSTM单元数量是两倍的
    def build_bidi_encoder_model():
        rnn = layers.LSTM
    
        # Encoder
        # encoder inputs
        encoder_inputs = Input(shape=(None,), name='encoder_inputs')
        # encoder embedding
        encoder_embedding = Embedding(num_encoder_tokens, encoder_embedding_dim,name='encoder_embedding')(encoder_inputs)
        # encoder lstm
        bidi_encoder_lstm = Bidirectional(rnn(latent_dim, return_state=True, dropout=0.2,recurrent_dropout=0.5), name='encoder_lstm')
        _, forward_h, forward_c, backward_h, backward_c = bidi_encoder_lstm(encoder_embedding)
        state_h = Concatenate()([forward_h, backward_h])
        state_c = Concatenate()([forward_c, backward_c])
        encoder_states = [state_h, state_c]
    
        # Decoder
        # decoder inputs
        decoder_inputs = Input(shape=(None,), name='decoder_inputs')
        # decoder embeddding
        decoder_embedding = Embedding(num_decoder_tokens, decoder_embedding_dim, name='decoder_embedding')(decoder_inputs)
        # decoder lstm, number of units is 2*latent_dim
        # NOTE THIS : latent_dim*2 for matching encoder_states
        decoder_lstm = rnn(latent_dim*2, return_state=True, 
                           return_sequences=True, dropout=0.2,
                           recurrent_dropout=0.5, name='decoder_lstm')
        # get outputs and decoder states
        rnn_outputs, *decoder_states = decoder_lstm(decoder_embedding, initial_state=encoder_states)
        # decoder dense
        decoder_dense = Dense(num_decoder_tokens, activation='softmax', name='decoder_dense')
        decoder_outputs = decoder_dense(rnn_outputs)
    
        bidi_encoder_model = Model([encoder_inputs,decoder_inputs], [decoder_outputs])
        bidi_encoder_model.compile(optimizer='adam', loss='categorical_crossentropy')
    
        return bidi_encoder_model

    训练双向编码器模型

    # 回调函数
    callback_list = [callbacks.ModelCheckpoint('bidi_encoder_model_best.h', save_best_only=True)]
    # 获取模型
    bidi_encoder_model = build_bidi_encoder_model()
    # 训练
    bidi_encoder_model_hist = bidi_encoder_model.fit([encoder_input_data, decoder_input_data], decoder_target_data,
                    batch_size=batch_size, epochs=epochs,
                    validation_split=0.2, callbacks=callback_list)
    Train on 40000 samples, validate on 10000 samples
    Epoch 1/20
    40000/40000 [==============================] - 66s 2ms/step - loss: 1.1616 - val_loss: 0.7842
    
    
    Epoch 2/20
    40000/40000 [==============================] - 53s 1ms/step - loss: 0.7496 - val_loss: 0.5850
    Epoch 3/20
    40000/40000 [==============================] - 58s 1ms/step - loss: 0.4799 - val_loss: 0.2103
    .....
    Epoch 20/20
    40000/40000 [==============================] - 61s 2ms/step - loss: 0.0016 - val_loss: 3.8348e-05
    
    def build_bidi_encoder_inference_model(model_path):
        model = load_model(model_path)
    
        # encoder
        encoder_inputs = Input(shape=(None,))
        # encoder_embedding
        encoder_embedding = model.get_layer('encoder_embedding')(encoder_inputs)
        # get encoder states
        _, forward_h, forward_c, backward_h, backward_c = model.get_layer('encoder_lstm')(encoder_embedding)
        state_h = Concatenate()([forward_h, backward_h])
        state_c = Concatenate()([forward_c, backward_c])
        encoder_states = [state_h, state_c]
        encoder_model = Model(encoder_inputs, encoder_states)
    
        # decoder
        # decoder inputs
        decoder_inputs = Input(shape=(None,))
        # decoder input states 
        decoder_state_h = Input(shape=(latent_dim*2,))
        decoder_state_c = Input(shape=(latent_dim*2,))
        decoder_states_inputs = [decoder_state_h, decoder_state_c]
    
        # decoder embedding
        decoder_embedding = model.get_layer('decoder_embedding')(decoder_inputs)
        # get rnn outputs and decoder states
        rnn_outputs, *decoder_states = model.get_layer('decoder_lstm')(decoder_embedding, initial_state=decoder_states_inputs)
        decoder_outputs = model.get_layer('decoder_dense')(rnn_outputs)
        decoder_model = Model([decoder_inputs] + decoder_states_inputs, [decoder_outputs]+decoder_states)
    
        return encoder_model, decoder_model
    model_path = 'bidi_encoder_model_best.h'
    inference_encoder_model, inference_decoder_model = build_bidi_encoder_inference_model(model_path)
    # 测试
    for seq_index in range(len(test_input_texts)):
        # Take one sequence (part of the training set)
        # for trying out decoding.
        input_seq = test_input_data[seq_index: seq_index + 1]
        decoded_sentence = decode_sequence(input_seq, inference_encoder_model, inference_decoder_model)
        print('-')
        print('Input sentence:', test_input_texts[seq_index])
        print('Decoded sentence:', decoded_sentence)
    -
    Input sentence: 59798
    Decoded sentence: 伍万玖仟柒佰玖拾捌元整终
    -
    Input sentence: 28307
    Decoded sentence: 贰万捌仟叁佰零柒元整终
    -
    Input sentence: 49323
    Decoded sentence: 肆万玖仟叁佰贰拾叁元整终
    -
    Input sentence: 24169
    Decoded sentence: 贰万肆仟壹佰陆拾玖元整终
    -
    Input sentence: 95323
    Decoded sentence: 玖万伍仟叁佰贰拾叁元整终
    -
    Input sentence: 50104
    Decoded sentence: 伍万零壹佰零肆元整终
    -
    Input sentence: 34650
    Decoded sentence: 叁万肆仟陆佰伍拾元整终
    -
    Input sentence: 60256
    Decoded sentence: 陆万零贰佰伍拾陆元整终
    -
    Input sentence: 42183
    Decoded sentence: 肆万贰仟壹佰捌拾叁元整终
    -
    Input sentence: 68802
    Decoded sentence: 陆万捌仟捌佰零贰元整终
    -
    Input sentence: 63819
    Decoded sentence: 陆万叁仟捌佰壹拾玖元整终
    -
    Input sentence: 32531
    Decoded sentence: 叁万贰仟伍佰叁拾壹元整终
    -
    Input sentence: 25678
    Decoded sentence: 贰万伍仟陆佰柒拾捌元整终
    -
    Input sentence: 42272
    Decoded sentence: 肆万贰仟贰佰柒拾贰元整终
    -
    Input sentence: 48908
    Decoded sentence: 肆万捌仟玖佰零捌元整终
    -
    Input sentence: 74546
    Decoded sentence: 柒万肆仟伍佰肆拾陆元整终
    -
    Input sentence: 11869
    Decoded sentence: 壹万壹仟捌佰陆拾玖元整终
    -
    Input sentence: 75803
    Decoded sentence: 柒万伍仟捌佰零叁元整终
    -
    Input sentence: 75727
    Decoded sentence: 柒万伍仟柒佰贰拾柒元整终
    -
    Input sentence: 67230
    Decoded sentence: 陆万柒仟贰佰叁拾元整终
    
    # 两种模型validation losss
    basic_model_val_loss = basic_model_hist.history['val_loss']
    bidi_model_val_loss = bidi_encoder_model_hist.history['val_loss']
    basic_model_train_loss = basic_model_hist.history['loss']
    bidi_model_train_loss = bidi_encoder_model_hist.history['loss']
    
    x_range = range(1, len(basic_model_val_loss)+1)
    plt.plot(x_range, basic_model_val_loss, 'r', label='Basic model validation loss')
    plt.plot(x_range, basic_model_train_loss, 'ro', label='Basic model Train loss')
    
    
    x_range = range(1, len(bidi_model_val_loss)+1)
    plt.plot(x_range, bidi_model_val_loss, 'b', label='Birirectianl model validation loss')
    plt.plot(x_range, bidi_model_train_loss, 'bo', label='Birirectianl model train loss')
    
    plt.plot()
    plt.xlabel('Epochs')
    plt.ylabel('Validation Loss')
    plt.legend()
    plt.show()

    png

    总结

    让我来总结下写代码时遇到的问题和坑

    1. 在实现双向编码器模型时,刚开始不知道如何将encoder的states作为decoder的初始状态,查了好一会才找到如何实现,并且似乎只有在keras 2.1.3以上版本有用,具体在 https://stackoverflow.com/questions/47923370/keras-bidirectional-lstm-seq2seq ,关键就是要将decoder的latent_dim*2
    2. 在预处理数据时,注意0的含义。在创建数据时,用的是np.zeros,如果0是代表着某个字符,那么训练将不正确,最好的办法是将0的含义设置为空
    3. 我还尝试着将decoder设计成双向的RNN,结果表明,训练阶段没有任何问题,能够得到很小的loss,但是在inference阶段,完全没有作用,因此我在想:是否在seq2seq模型中decoder只能是单向的
    4. 很明显,双向模型收敛速度快一些
    展开全文
  • 失业66

    万次阅读 多人点赞 2011-12-08 18:43:10
    10 点继续看书,看到 3 点左右睡觉。其实主要不过就是看一些 C++ 的基础知识,很多上学的时候还很熟练,现在确是都不会用了,我才觉得有时候工作会积累很多项目经验,但是有些东西被工作限制不用就会退化遗忘。 ...
      
    

    作为年轻人,我们苦心经营的无非两样——爱情和事业,拥有一份甜蜜的爱情能够为发展事业提供动力;而具有良好的事业更能为爱情提供保障,又或是成为追求爱情的资本。

     

    我们渴望着自己心仪的事业,或收入丰硕,或工作轻松,或增长见识,或结交人际。但是在很多时候,我们起初选择的工作并不是自己希望的,它们可能是走错的岔路,也可能是通往最终目标的阶梯。而在结束一份工作到选择一份新的工作的阶段这个必经过程就是失业。

     

    有些人的失业不过是预料之中的短暂过程:“下家我都找好了,这面完事简单准备下我就过那头入职了……”

     

    有些人的失业完全是不能选择的无奈:“我知道你工作挺努力,做事也很认真,但是公司现在不景气,需要一些人做出牺牲。你还年轻,有的是机会……”

     

    而有些人的失业其实是一时的冲动:“M  D别和我说那些没用的废话,告诉你老 子不干了,你爱找谁找谁去……”当然也可能是长久的积怨。

     

    …………

    “说说你为什么要辞职。是薪水问题?”

    “不是,我只是觉得一直写一些脚本得不到提高,想趁年轻学习写更深入的东西。”

    “那也不用辞职啊?你这么干着,找时间不一样学吗?”

    “……我是觉得工作中实践效果更好些,而且我也知道目前项目是后期,不会让我来练手,况且我手头还有工作的话时间上也不好分配。”

    “那你找到下家了?”

    “没有!”

    “要不你先继续干着,真是有更好的机会我也不勉强。”

    “很感谢,但是我觉得先离职更符合我的情况,我可能需要用一些时间来复习其他知识,然后才能去找工作。”

    “你这样其实有些极端,而且结果未必会像你想的那样。一个稳妥的方式是你等这个项目完成,大概半年左右吧,这样你或是在下个项目里接触些别的,或是再去找工作,这样有个完整的项目经验可能更好些。”

    “……半年我不能说我有多大提高,但我这个阶段还能学习的半年其实也没几个了。风险我也考虑过了,既然是自己的选择,我想我不会后悔。”

    …………

    “既然你已经决定了,我也没办法,准备下交接工作。要是你改主意了,我们再谈。”

    “好的。”

     

    一个月后,我离开了这家工作了一年半的公司,在我离开的前一天很多同事还不知道第二天我就不会来了,只有少数的一些人简单的聊了聊。我也不会像一些人那样搞个离别聚餐,本来我在公司也属于比较低调那种。况且我认为也没必要,因为像我这样项目做一半过来,没多久闪人的家伙,想来就像是各自航行的过程中,在一个码头停靠的船。短暂的相识后又会继续各自的航线。当然,有些可能还有机会相遇合作。

     

    离职对于我来说是预料之中的,好像是我计划了的,但又不知何时计划的。大学那时觉得自己喜欢做游戏,毕业后应该找份游戏开发的工作,但是门槛比较高,所以凭借对游戏的了解,加之学的程序找了份策划工作。后来公司程序人手不足,我就被临时调去帮忙,拐了个弯回到技术路线上来了。那时啥也不知道,看人家有经验的牛人真是不一样,于是立志要三五年也成为那种独当一面的游戏程序员。

     

    为了更好的发展,工作不到一年来到北京,但是仍是局限于做一些界面工作。不过想想,刚来不久机会还多,慢慢来。转眼一年半过去了,貌似没有太大的提高,每天早上起来都觉得时间流逝。觉得应该辞去这份工作,继续我成为合格游戏程序员的计划。

     

    就这样,累计入行两年多了,不满足于只做界面工作的我,在计划之中,却又完全没有下一步计划的情况下选择了辞职。所以我的失业是预料之中,却又充满未知的。

     

    1天:

    早上七点半,手机闹铃就在唱,习惯性的起来去刷牙、洗脸,之后好像时间静止了一分钟……我为啥要起来这么早?……不过已经起来了,就吃了点东西,开始在网上找各种电影看,什么都不做,只是宅在屋子里看到很晚~~~

     

    2天:

    今天起来很晚,上午已经被睡过去了,睡醒了第一感觉是有点饿了,于是收拾了一下出门。来到附近的一家小吃,平时都是晚上下班的时候来吃,人很多,有时没座位而且要等很久,而这个时候里面就我自己;路上的人也不像上下班高峰期那么多,觉得路好宽敞,人车都不慌不忙的走着。顺路去了附近的超市,里面人也不多,不是周末买东西结账都不用排队,一种悠闲的感觉油然而生。

     

    5天:

    最近各种电影电视剧是各种看啊,每天就是吃零食看电影,要说唯一的几次户外活动那就是出去吃饭,顺便再买点零食~~看的太多了,搞得上网都是找了半天,找出一个想看的。

    下午收到同学信息,问十一能不能回来,有个哥们结婚。我怎么回不去,我一个无业游民想回就回去,正好最近在这面也呆的无聊了,早些回家,免得十一不好买票。

     

    7天:

    今天回家,父母见我自然很是高兴,对于我工作上也是随我开心。啊 回家好啊,不用吃餐馆的快餐,想吃啥爹妈做好,当然我偶尔也自己弄点。娱乐活动依旧是看看电影,不同的是家里有电视,没事我也会趴在沙发上看看电视里特有的节目:各种广告、相亲、选秀,其中最具娱乐性的还是新闻节目~~

     

    9天:

    又一个高中同学今日大喜,一大早伙同另外几个哥们去参加,红包自然少不了,不过家乡属于一小城镇,虽说是结婚旺季,但花销我还是可以接受。婚礼形式很是套路,很多不过就一过场,我们去了也不过是借机会聚聚喝点酒相互捧捧。

    “听说你小子在北京混呢?大城市爽吧?”

    “啊,我一个打工,有什么好爽的,那地方到处都是人。房价巨高,房租也高,出门干什么都要排队,上地铁公交有时候还得靠身体…………”

    “不说有什么保障房,公租房啥的吗?新 闻都播了,很便宜。”

    “新 闻里的生活你也信?新 闻里人们多幸福,公 租 房那玩意,能随便住吗?那地方人那么多,你费个牛劲申请未必成功,成功了没准还得摇号。北京流行摇号,买车摇号,房子摇号,以后你想在那结婚 生 孩子?先去摇号~~ 哈哈哈”

    “那你还在那混,肯定还是好。”

    “哎,也谈不上好,不过就是机会多,对付吃穿不愁。你以为我没想过回老家吗?但是回来你说我干啥?做生意还没本钱,这地方最好就去事业单位,没关系能进去吗?大城市虽然生活纠结些,但毕竟还是相对凭能力说话的地方对吧”

    “也是,来干了~~~ 你现在是搞什么赚钱呢?”

    “大学学点程序,现在开发游戏。”

    “网游吗?啥游戏啊?”

    “啊,我之前那项目是XXX,有点像魔兽世界。还没上线你不能知道。”

    “哦,还没上线啊,能不能搞点内部的账号,或是外挂什么的。”

    “没有,你们这样的估计给你们,你们也未必玩,国产网游没钱玩你妹。”

    “恩,也是,啥都是要付费的,我是玩不起。不过你挺NB的肯定挣钱”

    “牛 逼还谈不上,目前还将长时间处于苦 逼阶段…………”

     

     

    12天:

    今天去一个亲戚家,期间难免打听下我的情况,刚听说在北京,觉得挺有出息,之后听说辞职回家了,言语间貌似是觉得我在那地方混不下去了。这让我感觉很不爽,但是也没心情和他解释,再说目前的确是失业阶段,说啥都是无力的,当时觉得在这个庸俗的时代,真是挣钱多就是成功。

     

    13天:

    在家闲了一星期,觉得自己应该看点书,学点东西了,不然怕是要把吃饭的本事都荒废了,想了想,不搞界面了肯定是要学C++啊,我这C++水平,哎,估计大学考试题能及格就不错了。不好好学是不行,于是,网上下载了份C++ primer 电子版开始一点点的学习。

     

    20天:

    学了有段时间了,每天就是中午起来,吃饭,下午看会书,晚上吃晚饭休息会,然后基本就是晚上910点继续看书,看到3点左右睡觉。其实主要不过就是看一些C++的基础知识,很多上学的时候还很熟练,现在确是都不会用了,我才觉得有时候工作会积累很多项目经验,但是有些东西被工作限制不用就会退化遗忘。

    今天为止看到一大半了,很多东西的理解也不像开始那么容易了。

     

    27天:

    每天半夜看书是效率最高的时候,周遭的环境是那么安静,若不是机箱的风扇嗡嗡作响,也许都能听到自己的呼吸和心跳的声音。老妈时不时的晚上过来看看我,叮嘱别太累,早点睡之类的关心。有次还颇有感慨的说我高考时候也没这么用功。

     

    高考?的确,其实我对上什么大学并不太关心,中学也不是那种一心学习的人,即使是高中最紧张的时候,网吧也是经常去的。当时的目标不过是找个差不多的学校,只要是学计算机就好。而现在则不同,我有更明确的学习目的,且所学的也是我追求的技术。另外,难道高考只是努力学习的一个终点?大学确实还好,不挂科不拿奖学金也不用疯狂学习,考研另当别论。想来即便是名牌学校毕业,如果就业后不学习也不见得就会发展的好,起码做程序应该是。

     

    半夜看书最好的是安静,最痛苦的是太安静。有时难免会觉得过于孤独,这份孤独是没人陪伴的孤独,父母虽在身边,但是很多方面是不希望他们知道的,何必让他们跟着操心呢?但在这种时候真的需要一些动力,或是熟睡中的女友,或是一同在努力的哥们。而我此时唯独能借以激励自己的就是那个毕业时的目标:成为一个合格的游戏程序员。

     

    31天:

    今天以前的同事打来电话,她是我决定离职后公司招来的刚毕业的,来接手我之前做的东西。她询问一些界面功能如何实现,我仔细的回想了下,然后给她详细说明了实现的方式。之后简单的聊了聊工作,我走后,那面工作都她来弄,压力看来比较大,这是她知道我在时能很好处理那么多繁琐的工作,还要经常和策划沟通是多么厉害。顿时让我觉得有种工作时的存在感。哎,看来是闲的太久应该回到工作上去了。

    空看了一堆C++的理论知识,不知道到底对我有多少帮助。但起码我已经是开始有所行动了,这是最重要的。我也知道做程序,最有效的学习方式是实践,但时间上不允许,我是希望在年前找份工作再回家过年的。现在看来,是时候回北京了,这样一面方便找工作,一面还可以继续学习。

    下午去车站买了车票,准备明天回去。

     

    33天:

    刚回来,收拾了下屋子,网上碰到几个同事,简单的聊聊,有的也已经跳槽了,工作都不错。自己也觉得是应该看看招聘信息了,于是按照自己的发展方向查了下相关的职位,发现自己的情况很尴尬:对于做游戏客户端而言,需要C++基础自然不用说,WINDOWS编程知识,设计模式的理解,乃至D3D图形知识……服务器同样,数据库,网络编程的掌握等等。相对来说现在自己的水平实在是太有限了,空有两年工作经验,此时却真的觉得自己什么都不知道。

    但知识是学出来的,高手也是从菜鸟练成的。自己能做的只能是继续学习,考虑到找工作会面对笔试,数据结构基本必考,好吧,先从数据结构入手,顺便也权当是简单用用C++的语言了。

     

    42天:

    近期又是看了很多理论知识:设计模式,简单了解了下设计模式是干什么用的,怎么分类,具体使用方式就先不详细研究了;网络,同样,看了看一些基本的概念,几个API都是怎么用的;WINDOWS编程,更是把一堆概念性的东西往脑袋里塞了塞,自己也知道,自己的脑子像内存,还是容量不大的那种,如果不用,这些东西几天就被释放掉了。不过没办法,要找工作是要写简历的,我总不能什么也不写啊,只写几个字:了解C++,一些脚本没了?谁会看这种简历?

     

    50天:

    今天终于决定不再看那些苦逼的理论知识了,当然也不是决定去做东西实践,现在的情况等我实践会了都明年了,要是把这些理论都掌握熟练了可能都到2012世界末日了,我可不想失业到地球毁灭。所以我决定写份简历。

    其实我写简历还是很在行的,因为我一般从看简历人的角度去写简历,我知道他们关注什么。而且我知道怎么样突出自己的优点,淡化缺点。诚信自然是必要的,简历内容真实是基本,但是语言是丰富的,看你怎么来用。我写简历一般要写很久,经常是一句话反复修改,这对于现在的我来说是很有必要的,如果你技术达到一定程度,自然就不依赖于这东西了,随便写点可能就被猎头瞄上了。

     

    52

    早上接到个电话,是猎头,通过我以前的同时知道我的,简单聊了聊。在知道我没有C++方面的经验却要转型后,他可能觉得也比较困难。之后就是简单的客套几句,说帮我留意下。我自然也没太在意。

    我了解自己的情况,和应届毕业上估计差不了多少,两年工作经验还比较纠结,从用人公司的角度来说,给什么价啊?当然了,只要脸皮厚,什么公司我还是都可以投的,反正也没损失对吧。所以我的计划是先从大公司投起,这样可能项目不是那么紧张,便于慢慢了解,另外,我也跳了两次了,现在如果环境允许,发展可以的话,其实我是打算找个好点的地方长期工作的。真是太好的去不了,再逐渐降档,应该最终会找到合适的。

    找来找去就先投了4家公司。

     

    53天:

    今天接到了很多笔试面试的电话,大概有56个,说来奇怪,大都是没听过的公司,只有一家公司是我之前投的4家之一。心想,可能是猎头帮忙联系的吧。可回去我试探的问了问发现不是他联系的,暂且不管了,反正有笔试面试就去看看,就当另外一种学习方式了。

     

    54天:

    近期第一次去面试,倒是没什么紧张感,去的是一家较大的欧美公司。安排在下午两点,到了后在前台登记了一下,然后给我份领到一个会议室去做题。一看试卷,哎,所有文字都是英文的,耐着性子看了看说明,意思是尽量用英文答题。心知英文水平比较糟烂,但是无所谓,起码能看懂题是什么,先看看题就当学习了。于是也慢慢答了一会,忽然接了个电话,是另外一家公司,笔试通知,我看了一眼日程表,近期都满了。看了一眼现在时间还不到3点,于是直接约3点半,然后交了卷匆匆去另外一家。

    这家公司以运营为主,研发只是辅助的一块。公司的技术主管临时有事不在,我等了一会看来他是回不来了,于是老板直接进行面试。他虽不做技术,但看的出来还是懂技术的,可能因为之前的笔试让我有点情绪,我在面试过程中一直都是说话比较直接。我说明了我的情况,然后还态度比较坚决的表示自己肯定就要做C++的东西,光写界面脚本不想再弄了。最后,对方的条件是,允许我写C++的逻辑相关的,然后还要去完成一些界面工作。我想了想还是同意了。

     

    55天:

    早上,起来打开邮箱,想看看今天的日程,忽然发现昨天下午那家公司居然已经发来offer了,3日之内答复。我回忆了下公司的项目,然后又考虑了下从事的工作,最后看了下公司的地理位置,离我住地确实很远,要挤地铁两个小时。哎,想来我未来还有满满10几个面试笔试安排,最终还是放弃了。不过我没有马上回复,觉得隔两天可能会显得我确实考虑过了。

    上午依旧有笔试面试的电话通知打过来,更诡异的是居然还有保险公司打来,说我应聘了什么销售经理的职位,还说觉得我简历比较合适!这都哪跟哪啊?这让我越发奇怪是怎么联系到我的,而且这样觉得完全打乱了我之前先从大公司入手的计划。最后,在招聘网站上找到了原因,原来我写完简历后,把简历弄成了托管状态,这样每天网站会帮我自动发送简历~~哎,看看最近满满的日程,我决定先关闭一段时间,不然再有通知都没时间去了。

    下午,去我自己选择的4家公司的另外一家,不知道当时怎么想的,居然投的是服务端开发,好吧我网络部分基本不会。公司离得也不是很近,到了也是标准流程,登记,笔试,面试~~笔试题我答的很快,题分为三部分,第一部分C++基础,第二部分 操作系统与网络 第三部分 各种游戏开发的实际问题。之所以答的快就是因为我会的不过就是第一部分。面试自然不用说,在对方皱着眉看完我的答案后。我就觉得已经没什么希望了,于是又是把自己的情况说了下,沟通间能够感觉到,对方还是比较欣赏我为人,包括经常玩游戏的经验,但是苦于没有C++开发经验的硬伤他也没办法。对方人确实不错,给了我一些建议,然后很客气的说有机会帮我联系下,我心里还是很感激的。

     

    63天:

    近期面试很累。每天到处跑,或答笔试题,或面试等等,去了有四五家公司,都是前些日子网站帮我投的简历,什么职位都有,也有我不想做的界面脚本,或是FLASH AS程序,我不是说AS程序有什么不好,可能是因为我一开始就喜欢用C++而工作却是AS所以我一直不太喜欢做AS。但现实往往就是这样,你越是不想做的东西,其实恰恰是优势。当我去面试界面程序或是AS开发的时候通常是这样的:

    “你工作经验还是不错的。”

    “我想从事C++相关的开发,逻辑或是服务器都可以,可能我没有这方面的经验会上手慢一点,但我还是有信心快速学习和适应工作的。”

    “你想做C++,又没有这方面的经验?”(他无法理解,觉得我是不是疯了)

    “是的,一直的工作都主要是界面相关的逻辑,我还是想接触更多的东西。”

    “语言的区别,其实关系不大,要一直写脚本也能练习基本功。”(我都练了两年多了)

    “恩,可能您觉得就逻辑而言语言关系不是很大,我做了两年的游戏工作了,我不想一直局限于从事界面工作。那么如果我想去做客户端图形方面的话,虽然是要学习D3D,但是显然C++是必要条件;同理,如果是服务器方向,网络或是服务器架构等等也是要有CC++知识,肯定不会让一个只会写脚本的人来做对吧?”

    “…………”(不知道他信不信,反正我一直信)

     

    而我也有自己的体会,面试过程中深刻认识到只做界面脚本没有C++经验是多么纠结,当我去面试C++开发的职位的时候通常是这样的情况:

    “你有两年半的工作经验?”(你有房子?)

    “恩,主要是从事界面逻辑的工作。”(一室一厅,还在还贷款)

    “哦,你熟悉C++,面向对象知识,数据结构?”(你有车?)

    “是的,系统的学习过相关知识,但是没有开发经验,我不能说掌握的多熟练。”(自行车,前几天撞树上了还在修呢)

    我真是已经有些麻木了,今天下午,我在一家公司,面试了3个部门,5个职位,笔试两次,面试5次,见了3HR和一个主管,历时5个小时,最后我已经身心俱疲,又累又饿。虽然笔试可能答的都还不错,面试问题回答的也都还可以,但基本都是上述情况。

    晚上,回去已经很晚了,草草的吃点东西,我看了一眼邮箱,里面还有七八家公司的面试通知,我查看了下明天的日程,两家公司的职位都是界面或AS相关的,于是直接客气的回复,通知下不去了,实在是没必要。我不过就是想做些C++相关的工作,难道真是我的想法错了?要从事服务器或是非界面工作的客户端就只能是从毕业开始就做CC++一直的做下去?现在想想很是后悔当时毕业的时候不够矜持,什么工作都做,为什么不直接找份C++的工作得了。非要选择条另类山路,先做策划,再去做界面,现在想做更深入的。哎~~

     

    64天:

    今天的面试都推掉了,昨天太累,而且连日来的经历我甚至开始怀疑自己的选择。但从另一个角度看更证明我不满足写界面脚本是对的。我坐在屋子里,安静的问自己:

    到底想要做什么?

    自然是一名合格的游戏开发程序员,或是服务器方面,或是客户端图形,这可能需要两到三年去实现。

    那么目前我最需要的是什么?

    是转型,使用语言的转型,从事工作的转型。

    那一个什么样的公司能适合我呢?

    首先是游戏公司,门槛不高,或项目不是很紧能够允许我去适应,一些大公司都不会这样。工资待遇只要差不多就可以了。最好是离得近,这样我有足够的时间去学习,可以经常在公司来学习或是工作。

    最后我在邮箱里看了下,把不符合的公司都回绝,只剩下了一家公司~~~

     

    65天:

    今天面试这家公司是我邮箱里剩下的最后一家,如果不成功,那我只能重新制定求职计划,甚至重新考虑发展方向问题,基本上年前就不会再找工作了。

    下午,我提前半小时出门坐车,公交3站就到了,如果不堵车应该10分钟就到,确实好近。没有笔试,登记了下就去面试,面试过程我觉得还算顺利,基本就是简单回答点问题,了解下情况。有了之前那么些公司面试的经验,我也比较直接,其实更多时候是我在表明一个态度,一个强烈的态度:我可以做这些工作,这就够了。至于我的工作经历,你可以当做一份个人素质的参考。之后公司高层也简单和我说了公司的情况:一个刚起步的IOS游戏公司。当时没太关心是IOS还是传统游戏公司,只要不让我写脚本就可以。

    回去后,和几个同学简单的聊聊,从他们介绍中了解IOS好像发展还不错,暗自想到如果可以就去这里吧。应该对我目前来说是最合适的了。

     

    66天:

    外面的大雾散去了,天晴了,很是明朗。

    上午10点,接到昨天公司的通知,面试已经通过了,一切手续从简,后天我就可以去报到了。于是结束了两个多月的失业日子,我又将迎来一个新的起点。我还算是如愿的找到了一份目前适合自己的工作,去探索一个全新的未知的领域,虽然难免会面临一些困难,但是我知道现在的我是航行在正确的道路上~~~

    最后也希望像我一样失业的人们,又或是面临就业的同学们,早日找到适合自己的工作。相信坚持正确的方向,困难不会阻挡我们前进,总会到达成功的彼岸!

     

    Hoist the Colours! Our world is wide!



    转载请注明来自:http://blog.csdn.net/zhao_yin



     
     
    展开全文
  • angularjs姓名拼音js

    千次阅读 2019-09-14 09:23:36
    angularjs姓名拼音js 姓名拼音HTML: 触发: ConvertPinyin('Basic'); <div class="form-item-input"> <div class="form-item-input-left"> ...

                                        angularjs姓名转拼音js

    姓名转拼音HTML:

    触发:  ConvertPinyin('Basic');

     <div class="form-item-input">
                    <div class="form-item-input-left">
                        <span>姓名: </span>
                    </div>
                    <div class="form-item-input-right">
                        <input style="margin-left: 0.1rem;" maxlength="20" placeholder="请输入姓名" v-model="creditRegistInfo.CustNm" name="CustNm" type="text" v-blur="ConvertPinyin('Basic')" required />
                    </div>
                </div>
                <div class="form-item-input">
                    <div class="form-item-input-left">
                        <span>姓名拼音: </span>
                    </div>
                    <div class="form-item-input-right">
                        <input style="margin-left: 0.1rem;" maxlength="20" placeholder="请核拼音是否准确" v-model="creditRegistInfo.UserNamePy" name="UserNamePy" type="text" required/>
                    </div>
                </div>

    姓名转拼音js: 

    触发:  ConvertPinyin('Basic'); 调用 quanpinyin.js中的 ConvertPinyin($scope.creditRegistInfo.CustNm);

      /**
         *姓名转拼音
         */
        $scope.ConvertPinyin = function (flag) {
            if (flag == "Basic" && $scope.creditRegistInfo.CustNm) {
                $scope.creditRegistInfo.UserNamePy = ConvertPinyin($scope.creditRegistInfo.CustNm);
            }
            else if (flag == "Secondary" && $scope.creditRegistInfo.FkName) {
                $scope.creditRegistInfo.FkNamePy = ConvertPinyin($scope.creditRegistInfo.FkName);
            }
        }

     quanpinyin.js:

    调用 quanpinyin.js中的 ConvertPinyin($scope.creditRegistInfo.CustNm);

    var PinYin = {
        "a": "\u554a\u963f\u9515",
        "ai": "\u57c3\u6328\u54ce\u5509\u54c0\u7691\u764c\u853c\u77ee\u827e\u788d\u7231\u9698\u8bf6\u6371\u55f3\u55cc\u5ad2\u7477\u66a7\u7839\u953f\u972d",
        "an": "\u978d\u6c28\u5b89\u4ffa\u6309\u6697\u5cb8\u80fa\u6848\u8c19\u57ef\u63de\u72b4\u5eb5\u6849\u94f5\u9e4c\u9878\u9eef",
        "ang": "\u80ae\u6602\u76ce",
        "ao": "\u51f9\u6556\u71ac\u7ff1\u8884\u50b2\u5965\u61ca\u6fb3\u5773\u62d7\u55f7\u5662\u5c99\u5ed2\u9068\u5aaa\u9a9c\u8071\u87af\u93ca\u9ccc\u93d6",
        "ba": "\u82ad\u634c\u6252\u53ed\u5427\u7b06\u516b\u75a4\u5df4\u62d4\u8dcb\u9776\u628a\u8019\u575d\u9738\u7f62\u7238\u8307\u83dd\u8406\u636d\u5c9c\u705e\u6777\u94af\u7c91\u9c85\u9b43",
        "bai": "\u767d\u67cf\u767e\u6446\u4f70\u8d25\u62dc\u7a17\u859c\u63b0\u97b4",
        "ban": "\u6591\u73ed\u642c\u6273\u822c\u9881\u677f\u7248\u626e\u62cc\u4f34\u74e3\u534a\u529e\u7eca\u962a\u5742\u8c73\u94a3\u7622\u764d\u8228",
        "bang": "\u90a6\u5e2e\u6886\u699c\u8180\u7ed1\u68d2\u78c5\u868c\u9551\u508d\u8c24\u84a1\u8783",
        "bao": "\u82de\u80de\u5305\u8912\u96f9\u4fdd\u5821\u9971\u5b9d\u62b1\u62a5\u66b4\u8c79\u9c8d\u7206\u52f9\u8446\u5b80\u5b62\u7172\u9e28\u8913\u8db5\u9f85",
        "bo": "\u5265\u8584\u73bb\u83e0\u64ad\u62e8\u94b5\u6ce2\u535a\u52c3\u640f\u94c2\u7b94\u4f2f\u5e1b\u8236\u8116\u818a\u6e24\u6cca\u9a73\u4eb3\u8543\u5575\u997d\u6a97\u64d8\u7934\u94b9\u9e41\u7c38\u8ddb",
        "bei": "\u676f\u7891\u60b2\u5351\u5317\u8f88\u80cc\u8d1d\u94a1\u500d\u72c8\u5907\u60eb\u7119\u88ab\u5b5b\u9642\u90b6\u57e4\u84d3\u5457\u602b\u6096\u789a\u9e4e\u8919\u943e",
        "ben": "\u5954\u82ef\u672c\u7b28\u755a\u574c\u951b",
        "beng": "\u5d29\u7ef7\u752d\u6cf5\u8e66\u8ff8\u552a\u5623\u750f",
        "bi": "\u903c\u9f3b\u6bd4\u9119\u7b14\u5f7c\u78a7\u84d6\u853d\u6bd5\u6bd9\u6bd6\u5e01\u5e87\u75f9\u95ed\u655d\u5f0a\u5fc5\u8f9f\u58c1\u81c2\u907f\u965b\u5315\u4ef3\u4ffe\u8298\u835c\u8378\u5421\u54d4\u72f4\u5eb3\u610e\u6ed7\u6fde\u5f3c\u59a3\u5a62\u5b16\u74a7\u8d32\u7540\u94cb\u79d5\u88e8\u7b5a\u7b85\u7be6\u822d\u895e\u8df8\u9ac0",
        "bian": "\u97ad\u8fb9\u7f16\u8d2c\u6241\u4fbf\u53d8\u535e\u8fa8\u8fa9\u8fab\u904d\u533e\u5f01\u82c4\u5fed\u6c74\u7f0f\u7178\u782d\u78a5\u7a39\u7a86\u8759\u7b3e\u9cca",
        "biao": "\u6807\u5f6a\u8198\u8868\u5a4a\u9aa0\u98d1\u98d9\u98da\u706c\u9556\u9573\u762d\u88f1\u9cd4",
        "bie": "\u9cd6\u618b\u522b\u762a\u8e69\u9cd8",
        "bin": "\u5f6c\u658c\u6fd2\u6ee8\u5bbe\u6448\u50a7\u6d5c\u7f24\u73a2\u6ba1\u8191\u9554\u9acc\u9b13",
        "bing": "\u5175\u51b0\u67c4\u4e19\u79c9\u997c\u70b3\u75c5\u5e76\u7980\u90b4\u6452\u7ee0\u678b\u69df\u71f9",
        "bu": "\u6355\u535c\u54fa\u8865\u57e0\u4e0d\u5e03\u6b65\u7c3f\u90e8\u6016\u62ca\u535f\u900b\u74ff\u6661\u949a\u91ad",
        "ca": "\u64e6\u5693\u7924",
        "cai": "\u731c\u88c1\u6750\u624d\u8d22\u776c\u8e29\u91c7\u5f69\u83dc\u8521",
        "can": "\u9910\u53c2\u8695\u6b8b\u60ed\u60e8\u707f\u9a96\u74a8\u7cb2\u9eea",
        "cang": "\u82cd\u8231\u4ed3\u6ca7\u85cf\u4f27",
        "cao": "\u64cd\u7cd9\u69fd\u66f9\u8349\u8279\u5608\u6f15\u87ac\u825a",
        "ce": "\u5395\u7b56\u4fa7\u518c\u6d4b\u5202\u5e3b\u607b",
        "ceng": "\u5c42\u8e6d\u564c",
        "cha": "\u63d2\u53c9\u832c\u8336\u67e5\u78b4\u643d\u5bdf\u5c94\u5dee\u8be7\u7339\u9987\u6c4a\u59f9\u6748\u6942\u69ce\u6aab\u9497\u9538\u9572\u8869",
        "chai": "\u62c6\u67f4\u8c7a\u4faa\u8308\u7625\u867f\u9f87",
        "chan": "\u6400\u63ba\u8749\u998b\u8c17\u7f20\u94f2\u4ea7\u9610\u98a4\u5181\u8c04\u8c36\u8487\u5edb\u5fcf\u6f7a\u6fb6\u5b71\u7fbc\u5a75\u5b17\u9aa3\u89c7\u7985\u9561\u88e3\u87fe\u8e94",
        "chang": "\u660c\u7316\u573a\u5c1d\u5e38\u957f\u507f\u80a0\u5382\u655e\u7545\u5531\u5021\u4f25\u9b2f\u82cc\u83d6\u5f9c\u6005\u60dd\u960a\u5a3c\u5ae6\u6636\u6c05\u9cb3",
        "chao": "\u8d85\u6284\u949e\u671d\u5632\u6f6e\u5de2\u5435\u7092\u600a\u7ec9\u6641\u8016",
        "che": "\u8f66\u626f\u64a4\u63a3\u5f7b\u6f88\u577c\u5c6e\u7817",
        "chen": "\u90f4\u81e3\u8fb0\u5c18\u6668\u5ff1\u6c89\u9648\u8d81\u886c\u79f0\u8c0c\u62bb\u55d4\u5bb8\u741b\u6987\u809c\u80c2\u789c\u9f80",
        "cheng": "\u6491\u57ce\u6a59\u6210\u5448\u4e58\u7a0b\u60e9\u6f84\u8bda\u627f\u901e\u9a8b\u79e4\u57d5\u5d4a\u5fb5\u6d48\u67a8\u67fd\u6a18\u665f\u584d\u77a0\u94d6\u88ce\u86cf\u9172",
        "chi": "\u5403\u75f4\u6301\u5319\u6c60\u8fdf\u5f1b\u9a70\u803b\u9f7f\u4f88\u5c3a\u8d64\u7fc5\u65a5\u70bd\u50ba\u5880\u82aa\u830c\u640b\u53f1\u54e7\u557b\u55e4\u5f73\u996c\u6cb2\u5ab8\u6555\u80dd\u7719\u7735\u9e31\u761b\u892b\u86a9\u87ad\u7b1e\u7bea\u8c49\u8e05\u8e1f\u9b51",
        "chong": "\u5145\u51b2\u866b\u5d07\u5ba0\u833a\u5fe1\u61a7\u94f3\u825f",
        "chou": "\u62bd\u916c\u7574\u8e0c\u7a20\u6101\u7b79\u4ec7\u7ef8\u7785\u4e11\u4fe6\u5733\u5e31\u60c6\u6eb4\u59af\u7633\u96e0\u9c8b",
        "chu": "\u81ed\u521d\u51fa\u6a71\u53a8\u8e87\u9504\u96cf\u6ec1\u9664\u695a\u7840\u50a8\u77d7\u6410\u89e6\u5904\u4e8d\u520d\u61b7\u7ecc\u6775\u696e\u6a17\u870d\u8e70\u9edc",
        "chuan": "\u63e3\u5ddd\u7a7f\u693d\u4f20\u8239\u5598\u4e32\u63be\u821b\u60f4\u9044\u5ddb\u6c1a\u948f\u9569\u8221",
        "chuang": "\u75ae\u7a97\u5e62\u5e8a\u95ef\u521b\u6006",
        "chui": "\u5439\u708a\u6376\u9524\u5782\u9672\u68f0\u69cc",
        "chun": "\u6625\u693f\u9187\u5507\u6df3\u7eaf\u8822\u4fc3\u83bc\u6c8c\u80ab\u6710\u9e51\u877d",
        "chuo": "\u6233\u7ef0\u851f\u8fb6\u8f8d\u955e\u8e14\u9f8a",
        "ci": "\u75b5\u8328\u78c1\u96cc\u8f9e\u6148\u74f7\u8bcd\u6b64\u523a\u8d50\u6b21\u8360\u5472\u5d6f\u9e5a\u8785\u7ccd\u8d91",
        "cong": "\u806a\u8471\u56f1\u5306\u4ece\u4e1b\u506c\u82c1\u6dd9\u9aa2\u742e\u7481\u679e",
        "cu": "\u51d1\u7c97\u918b\u7c07\u731d\u6b82\u8e59",
        "cuan": "\u8e7f\u7be1\u7a9c\u6c46\u64ba\u6615\u7228",
        "cui": "\u6467\u5d14\u50ac\u8106\u7601\u7cb9\u6dec\u7fe0\u8403\u60b4\u7480\u69b1\u96b9",
        "cun": "\u6751\u5b58\u5bf8\u78cb\u5fd6\u76b4",
        "cuo": "\u64ae\u6413\u63aa\u632b\u9519\u539d\u811e\u9509\u77ec\u75e4\u9e7e\u8e49\u8e9c",
        "da": "\u642d\u8fbe\u7b54\u7629\u6253\u5927\u8037\u54d2\u55d2\u601b\u59b2\u75b8\u8921\u7b2a\u977c\u9791",
        "dai": "\u5446\u6b79\u50a3\u6234\u5e26\u6b86\u4ee3\u8d37\u888b\u5f85\u902e\u6020\u57ed\u7519\u5454\u5cb1\u8fe8\u902f\u9a80\u7ed0\u73b3\u9edb",
        "dan": "\u803d\u62c5\u4e39\u5355\u90f8\u63b8\u80c6\u65e6\u6c2e\u4f46\u60ee\u6de1\u8bde\u5f39\u86cb\u4ebb\u510b\u5369\u840f\u5556\u6fb9\u6a90\u6b9a\u8d55\u7708\u7605\u8043\u7baa",
        "dang": "\u5f53\u6321\u515a\u8361\u6863\u8c20\u51fc\u83ea\u5b95\u7800\u94db\u88c6",
        "dao": "\u5200\u6363\u8e48\u5012\u5c9b\u7977\u5bfc\u5230\u7a3b\u60bc\u9053\u76d7\u53e8\u5541\u5fc9\u6d2e\u6c18\u7118\u5fd1\u7e9b",
        "de": "\u5fb7\u5f97\u7684\u951d",
        "deng": "\u8e6c\u706f\u767b\u7b49\u77aa\u51f3\u9093\u5654\u5d9d\u6225\u78f4\u956b\u7c26",
        "di": "\u5824\u4f4e\u6ef4\u8fea\u654c\u7b1b\u72c4\u6da4\u7fdf\u5ae1\u62b5\u5e95\u5730\u8482\u7b2c\u5e1d\u5f1f\u9012\u7f14\u6c10\u7c74\u8bcb\u8c1b\u90b8\u577b\u839c\u837b\u5600\u5a23\u67e2\u68e3\u89cc\u7825\u78b2\u7747\u955d\u7f9d\u9ab6",
        "dian": "\u98a0\u6382\u6ec7\u7898\u70b9\u5178\u975b\u57ab\u7535\u4f43\u7538\u5e97\u60e6\u5960\u6dc0\u6bbf\u4e36\u963d\u576b\u57dd\u5dc5\u73b7\u765c\u766b\u7c1f\u8e2e",
        "diao": "\u7889\u53fc\u96d5\u51cb\u5201\u6389\u540a\u9493\u8c03\u8f7a\u94de\u8729\u7c9c\u8c82",
        "die": "\u8dcc\u7239\u789f\u8776\u8fed\u8c0d\u53e0\u4f5a\u57a4\u581e\u63f2\u558b\u6e2b\u8f76\u7252\u74de\u8936\u800b\u8e40\u9cbd\u9cce",
        "ding": "\u4e01\u76ef\u53ee\u9489\u9876\u9f0e\u952d\u5b9a\u8ba2\u4e22\u4ec3\u5576\u738e\u815a\u7887\u753a\u94e4\u7594\u8035\u914a",
        "dong": "\u4e1c\u51ac\u8463\u61c2\u52a8\u680b\u4f97\u606b\u51bb\u6d1e\u578c\u549a\u5cbd\u5cd2\u5902\u6c21\u80e8\u80f4\u7850\u9e2b",
        "dou": "\u515c\u6296\u6597\u9661\u8c46\u9017\u75d8\u8538\u94ad\u7aa6\u7aac\u86aa\u7bfc\u9161",
        "du": "\u90fd\u7763\u6bd2\u728a\u72ec\u8bfb\u5835\u7779\u8d4c\u675c\u9540\u809a\u5ea6\u6e21\u5992\u828f\u561f\u6e0e\u691f\u6a50\u724d\u8839\u7b03\u9ad1\u9ee9",
        "duan": "\u7aef\u77ed\u953b\u6bb5\u65ad\u7f0e\u5f56\u6934\u7145\u7c16",
        "dui": "\u5806\u5151\u961f\u5bf9\u603c\u619d\u7893",
        "dun": "\u58a9\u5428\u8e72\u6566\u987f\u56e4\u949d\u76fe\u9041\u7096\u7818\u7905\u76f9\u9566\u8db8",
        "duo": "\u6387\u54c6\u591a\u593a\u579b\u8eb2\u6735\u8dfa\u8235\u5241\u60f0\u5815\u5484\u54da\u7f0d\u67c1\u94ce\u88f0\u8e31",
        "e": "\u86fe\u5ce8\u9e45\u4fc4\u989d\u8bb9\u5a25\u6076\u5384\u627c\u904f\u9102\u997f\u5669\u8c14\u57a9\u57ad\u82ca\u83aa\u843c\u5443\u6115\u5c59\u5a40\u8f6d\u66f7\u816d\u786a\u9507\u9537\u9e57\u989a\u9cc4",
        "en": "\u6069\u84bd\u6441\u5514\u55ef",
        "er": "\u800c\u513f\u8033\u5c14\u9975\u6d31\u4e8c\u8d30\u8fe9\u73e5\u94d2\u9e38\u9c95",
        "fa": "\u53d1\u7f5a\u7b4f\u4f10\u4e4f\u9600\u6cd5\u73d0\u57a1\u781d",
        "fan": "\u85e9\u5e06\u756a\u7ffb\u6a0a\u77fe\u9492\u7e41\u51e1\u70e6\u53cd\u8fd4\u8303\u8d29\u72af\u996d\u6cdb\u8629\u5e61\u72ad\u68b5\u6535\u71d4\u7548\u8e6f",
        "fang": "\u574a\u82b3\u65b9\u80aa\u623f\u9632\u59a8\u4eff\u8bbf\u7eba\u653e\u531a\u90a1\u5f77\u94ab\u822b\u9c82",
        "fei": "\u83f2\u975e\u5561\u98de\u80a5\u532a\u8bfd\u5420\u80ba\u5e9f\u6cb8\u8d39\u82be\u72d2\u60b1\u6ddd\u5983\u7ecb\u7eef\u69a7\u8153\u6590\u6249\u7953\u7829\u9544\u75f1\u871a\u7bda\u7fe1\u970f\u9cb1",
        "fen": "\u82ac\u915a\u5429\u6c1b\u5206\u7eb7\u575f\u711a\u6c7e\u7c89\u594b\u4efd\u5fff\u6124\u7caa\u507e\u7035\u68fc\u610d\u9cbc\u9f22",
        "feng": "\u4e30\u5c01\u67ab\u8702\u5cf0\u950b\u98ce\u75af\u70fd\u9022\u51af\u7f1d\u8bbd\u5949\u51e4\u4ff8\u9146\u8451\u6ca3\u781c",
        "fu": "\u4f5b\u5426\u592b\u6577\u80a4\u5b75\u6276\u62c2\u8f90\u5e45\u6c1f\u7b26\u4f0f\u4fd8\u670d\u6d6e\u6daa\u798f\u88b1\u5f17\u752b\u629a\u8f85\u4fef\u91dc\u65a7\u812f\u8151\u5e9c\u8150\u8d74\u526f\u8986\u8d4b\u590d\u5085\u4ed8\u961c\u7236\u8179\u8d1f\u5bcc\u8ba3\u9644\u5987\u7f1a\u5490\u5310\u51eb\u90db\u8299\u82fb\u832f\u83a9\u83d4\u544b\u5e5e\u6ecf\u8274\u5b5a\u9a78\u7ec2\u6874\u8d59\u9efb\u9efc\u7f58\u7a03\u99a5\u864d\u86a8\u8709\u8760\u876e\u9eb8\u8dba\u8dd7\u9cc6",
        "ga": "\u5676\u560e\u86e4\u5c2c\u5477\u5c15\u5c1c\u65ee\u9486",
        "gai": "\u8be5\u6539\u6982\u9499\u76d6\u6e89\u4e10\u9654\u5793\u6224\u8d45\u80f2",
        "gan": "\u5e72\u7518\u6746\u67d1\u7aff\u809d\u8d76\u611f\u79c6\u6562\u8d63\u5769\u82f7\u5c34\u64c0\u6cd4\u6de6\u6f89\u7ec0\u6a44\u65f0\u77f8\u75b3\u9150",
        "gang": "\u5188\u521a\u94a2\u7f38\u809b\u7eb2\u5c97\u6e2f\u6206\u7f61\u9883\u7b7b",
        "gong": "\u6760\u5de5\u653b\u529f\u606d\u9f9a\u4f9b\u8eac\u516c\u5bab\u5f13\u5de9\u6c5e\u62f1\u8d21\u5171\u857b\u5efe\u54a3\u73d9\u80b1\u86a3\u86e9\u89e5",
        "gao": "\u7bd9\u768b\u9ad8\u818f\u7f94\u7cd5\u641e\u9550\u7a3f\u544a\u777e\u8bf0\u90dc\u84bf\u85c1\u7f1f\u69d4\u69c1\u6772\u9506",
        "ge": "\u54e5\u6b4c\u6401\u6208\u9e3d\u80f3\u7599\u5272\u9769\u845b\u683c\u9601\u9694\u94ec\u4e2a\u5404\u9b32\u4ee1\u54ff\u5865\u55dd\u7ea5\u643f\u8188\u784c\u94ea\u9549\u88bc\u988c\u867c\u8238\u9abc\u9ac2",
        "gei": "\u7ed9",
        "gen": "\u6839\u8ddf\u4e98\u831b\u54cf\u826e",
        "geng": "\u8015\u66f4\u5e9a\u7fb9\u57c2\u803f\u6897\u54fd\u8d53\u9ca0",
        "gou": "\u94a9\u52fe\u6c9f\u82df\u72d7\u57a2\u6784\u8d2d\u591f\u4f5d\u8bdf\u5ca3\u9058\u5abe\u7f11\u89cf\u5f40\u9e32\u7b31\u7bdd\u97b2",
        "gu": "\u8f9c\u83c7\u5495\u7b8d\u4f30\u6cbd\u5b64\u59d1\u9f13\u53e4\u86ca\u9aa8\u8c37\u80a1\u6545\u987e\u56fa\u96c7\u560f\u8bc2\u83f0\u54cc\u5d2e\u6c69\u688f\u8f71\u726f\u727f\u80cd\u81cc\u6bc2\u77bd\u7f5f\u94b4\u9522\u74e0\u9e2a\u9e44\u75fc\u86c4\u9164\u89da\u9cb4\u9ab0\u9e58",
        "gua": "\u522e\u74dc\u5250\u5be1\u6302\u8902\u5366\u8bd6\u5471\u681d\u9e39",
        "guai": "\u4e56\u62d0\u602a\u54d9",
        "guan": "\u68fa\u5173\u5b98\u51a0\u89c2\u7ba1\u9986\u7f50\u60ef\u704c\u8d2f\u500c\u839e\u63bc\u6dab\u76e5\u9e73\u9ccf",
        "guang": "\u5149\u5e7f\u901b\u72b7\u6844\u80f1\u7592",
        "gui": "\u7470\u89c4\u572d\u7845\u5f52\u9f9f\u95fa\u8f68\u9b3c\u8be1\u7678\u6842\u67dc\u8dea\u8d35\u523d\u5326\u523f\u5e8b\u5b84\u59ab\u6867\u7085\u6677\u7688\u7c0b\u9c91\u9cdc",
        "gun": "\u8f8a\u6eda\u68cd\u4e28\u886e\u7ef2\u78d9\u9ca7",
        "guo": "\u9505\u90ed\u56fd\u679c\u88f9\u8fc7\u9998\u8803\u57da\u63b4\u5459\u56d7\u5e3c\u5d1e\u7313\u6901\u8662\u951e\u8052\u872e\u873e\u8748",
        "ha": "\u54c8",
        "hai": "\u9ab8\u5b69\u6d77\u6c26\u4ea5\u5bb3\u9a87\u54b4\u55e8\u988f\u91a2",
        "han": "\u9163\u61a8\u90af\u97e9\u542b\u6db5\u5bd2\u51fd\u558a\u7f55\u7ff0\u64bc\u634d\u65f1\u61be\u608d\u710a\u6c57\u6c49\u9097\u83e1\u6496\u961a\u701a\u6657\u7113\u9894\u86b6\u9f3e",
        "hen": "\u592f\u75d5\u5f88\u72e0\u6068",
        "hang": "\u676d\u822a\u6c86\u7ed7\u73e9\u6841",
        "hao": "\u58d5\u568e\u8c6a\u6beb\u90dd\u597d\u8017\u53f7\u6d69\u8585\u55e5\u5686\u6fe0\u704f\u660a\u7693\u98a2\u869d",
        "he": "\u5475\u559d\u8377\u83cf\u6838\u79be\u548c\u4f55\u5408\u76d2\u8c89\u9602\u6cb3\u6db8\u8d6b\u8910\u9e64\u8d3a\u8bc3\u52be\u58d1\u85ff\u55d1\u55ec\u9616\u76cd\u86b5\u7fee",
        "hei": "\u563f\u9ed1",
        "heng": "\u54fc\u4ea8\u6a2a\u8861\u6052\u8a07\u8605",
        "hong": "\u8f70\u54c4\u70d8\u8679\u9e3f\u6d2a\u5b8f\u5f18\u7ea2\u9ec9\u8ba7\u836d\u85a8\u95f3\u6cd3",
        "hou": "\u5589\u4faf\u7334\u543c\u539a\u5019\u540e\u5820\u5f8c\u9005\u760a\u7bcc\u7cc7\u9c8e\u9aba",
        "hu": "\u547c\u4e4e\u5ffd\u745a\u58f6\u846b\u80e1\u8774\u72d0\u7cca\u6e56\u5f27\u864e\u552c\u62a4\u4e92\u6caa\u6237\u51b1\u553f\u56eb\u5cb5\u7322\u6019\u60da\u6d52\u6ef9\u7425\u69f2\u8f77\u89f3\u70c0\u7173\u623d\u6248\u795c\u9e55\u9e71\u7b0f\u9190\u659b",
        "hua": "\u82b1\u54d7\u534e\u733e\u6ed1\u753b\u5212\u5316\u8bdd\u5290\u6d4d\u9a85\u6866\u94e7\u7a1e",
        "huai": "\u69d0\u5f8a\u6000\u6dee\u574f\u8fd8\u8e1d",
        "huan": "\u6b22\u73af\u6853\u7f13\u6362\u60a3\u5524\u75ea\u8c62\u7115\u6da3\u5ba6\u5e7b\u90c7\u5942\u57b8\u64d0\u571c\u6d39\u6d63\u6f36\u5bf0\u902d\u7f33\u953e\u9ca9\u9b1f",
        "huang": "\u8352\u614c\u9ec4\u78fa\u8757\u7c27\u7687\u51f0\u60f6\u714c\u6643\u5e4c\u604d\u8c0e\u968d\u5fa8\u6e5f\u6f62\u9051\u749c\u8093\u7640\u87e5\u7bc1\u9cc7",
        "hui": "\u7070\u6325\u8f89\u5fbd\u6062\u86d4\u56de\u6bc1\u6094\u6167\u5349\u60e0\u6666\u8d3f\u79fd\u4f1a\u70e9\u6c47\u8bb3\u8bf2\u7ed8\u8bd9\u8334\u835f\u8559\u54d5\u5599\u96b3\u6d04\u5f57\u7f0b\u73f2\u6656\u605a\u867a\u87ea\u9ebe",
        "hun": "\u8364\u660f\u5a5a\u9b42\u6d51\u6df7\u8be8\u9984\u960d\u6eb7\u7f17",
        "huo": "\u8c41\u6d3b\u4f19\u706b\u83b7\u6216\u60d1\u970d\u8d27\u7978\u6509\u56af\u5925\u94ac\u952a\u956c\u8020\u8816",
        "ji": "\u51fb\u573e\u57fa\u673a\u7578\u7a3d\u79ef\u7b95\u808c\u9965\u8ff9\u6fc0\u8ba5\u9e21\u59ec\u7ee9\u7f09\u5409\u6781\u68d8\u8f91\u7c4d\u96c6\u53ca\u6025\u75be\u6c72\u5373\u5ac9\u7ea7\u6324\u51e0\u810a\u5df1\u84df\u6280\u5180\u5b63\u4f0e\u796d\u5242\u60b8\u6d4e\u5bc4\u5bc2\u8ba1\u8bb0\u65e2\u5fcc\u9645\u5993\u7ee7\u7eaa\u5c45\u4e0c\u4e69\u525e\u4f76\u4f74\u8114\u58bc\u82a8\u82b0\u8401\u84ba\u857a\u638e\u53fd\u54ad\u54dc\u5527\u5c8c\u5d74\u6d0e\u5f50\u5c50\u9aa5\u757f\u7391\u696b\u6b9b\u621f\u6222\u8d4d\u89ca\u7284\u9f51\u77f6\u7f81\u5d47\u7a37\u7620\u7635\u866e\u7b08\u7b04\u66a8\u8dfb\u8dfd\u9701\u9c9a\u9cab\u9afb\u9e82",
        "jia": "\u5609\u67b7\u5939\u4f73\u5bb6\u52a0\u835a\u988a\u8d3e\u7532\u94be\u5047\u7a3c\u4ef7\u67b6\u9a7e\u5ac1\u4f3d\u90cf\u62ee\u5cac\u6d43\u8fe6\u73c8\u621b\u80db\u605d\u94d7\u9553\u75c2\u86f1\u7b33\u8888\u8dcf",
        "jian": "\u6b7c\u76d1\u575a\u5c16\u7b3a\u95f4\u714e\u517c\u80a9\u8270\u5978\u7f04\u8327\u68c0\u67ec\u78b1\u7877\u62e3\u6361\u7b80\u4fed\u526a\u51cf\u8350\u69db\u9274\u8df5\u8d31\u89c1\u952e\u7bad\u4ef6\u5065\u8230\u5251\u996f\u6e10\u6e85\u6da7\u5efa\u50ed\u8c0f\u8c2b\u83c5\u84b9\u641b\u56dd\u6e54\u8e47\u8b07\u7f23\u67a7\u67d9\u6957\u620b\u622c\u726e\u728d\u6bfd\u8171\u7751\u950f\u9e63\u88e5\u7b15\u7bb4\u7fe6\u8dbc\u8e3a\u9ca3\u97af",
        "jiang": "\u50f5\u59dc\u5c06\u6d46\u6c5f\u7586\u848b\u6868\u5956\u8bb2\u5320\u9171\u964d\u8333\u6d1a\u7edb\u7f30\u729f\u7913\u8029\u7ce8\u8c47",
        "jiao": "\u8549\u6912\u7901\u7126\u80f6\u4ea4\u90ca\u6d47\u9a84\u5a07\u56bc\u6405\u94f0\u77eb\u4fa5\u811a\u72e1\u89d2\u997a\u7f34\u7ede\u527f\u6559\u9175\u8f7f\u8f83\u53eb\u4f7c\u50ec\u832d\u6322\u564d\u5ce4\u5fbc\u59e3\u7e9f\u656b\u768e\u9e6a\u86df\u91ae\u8de4\u9c9b",
        "jie": "\u7a96\u63ed\u63a5\u7686\u79f8\u8857\u9636\u622a\u52ab\u8282\u6854\u6770\u6377\u776b\u7aed\u6d01\u7ed3\u89e3\u59d0\u6212\u85c9\u82a5\u754c\u501f\u4ecb\u75a5\u8beb\u5c4a\u5048\u8ba6\u8bd8\u5588\u55df\u736c\u5a55\u5b51\u6840\u7352\u78a3\u9534\u7596\u88b7\u9889\u86a7\u7faf\u9c92\u9ab1\u9aeb",
        "jin": "\u5dfe\u7b4b\u65a4\u91d1\u4eca\u6d25\u895f\u7d27\u9526\u4ec5\u8c28\u8fdb\u9773\u664b\u7981\u8fd1\u70ec\u6d78\u5c3d\u537a\u8369\u5807\u5664\u9991\u5ed1\u5997\u7f19\u747e\u69ff\u8d46\u89d0\u9485\u9513\u887f\u77dc",
        "jing": "\u52b2\u8346\u5162\u830e\u775b\u6676\u9cb8\u4eac\u60ca\u7cbe\u7cb3\u7ecf\u4e95\u8b66\u666f\u9888\u9759\u5883\u656c\u955c\u5f84\u75c9\u9756\u7adf\u7ade\u51c0\u522d\u5106\u9631\u83c1\u734d\u61ac\u6cfe\u8ff3\u5f2a\u5a67\u80bc\u80eb\u8148\u65cc",
        "jiong": "\u70af\u7a98\u5182\u8fe5\u6243",
        "jiu": "\u63ea\u7a76\u7ea0\u7396\u97ed\u4e45\u7078\u4e5d\u9152\u53a9\u6551\u65e7\u81fc\u8205\u548e\u5c31\u759a\u50e6\u557e\u9604\u67e9\u6855\u9e6b\u8d73\u9b0f",
        "ju": "\u97a0\u62d8\u72d9\u75bd\u9a79\u83ca\u5c40\u5480\u77e9\u4e3e\u6cae\u805a\u62d2\u636e\u5de8\u5177\u8ddd\u8e1e\u952f\u4ff1\u53e5\u60e7\u70ac\u5267\u5028\u8bb5\u82e3\u82f4\u8392\u63ac\u907d\u5c66\u741a\u67b8\u6910\u6998\u6989\u6a58\u728b\u98d3\u949c\u9514\u7aad\u88fe\u8d84\u91b5\u8e3d\u9f83\u96ce\u97ab",
        "juan": "\u6350\u9e43\u5a1f\u5026\u7737\u5377\u7ee2\u9104\u72f7\u6d93\u684a\u8832\u9529\u954c\u96bd",
        "jue": "\u6485\u652b\u6289\u6398\u5014\u7235\u89c9\u51b3\u8bc0\u7edd\u53a5\u5282\u8c32\u77cd\u8568\u5658\u5d1b\u7357\u5b53\u73cf\u6877\u6a5b\u721d\u9562\u8e76\u89d6",
        "jun": "\u5747\u83cc\u94a7\u519b\u541b\u5cfb\u4fca\u7ae3\u6d5a\u90e1\u9a8f\u6343\u72fb\u76b2\u7b60\u9e87",
        "ka": "\u5580\u5496\u5361\u4f67\u5494\u80e9",
        "ke": "\u54af\u5777\u82db\u67ef\u68f5\u78d5\u9897\u79d1\u58f3\u54b3\u53ef\u6e34\u514b\u523b\u5ba2\u8bfe\u5ca2\u606a\u6e98\u9a92\u7f02\u73c2\u8f72\u6c2a\u778c\u94b6\u75b4\u7aa0\u874c\u9ac1",
        "kai": "\u5f00\u63e9\u6977\u51ef\u6168\u5240\u57b2\u8488\u5ffe\u607a\u94e0\u950e",
        "kan": "\u520a\u582a\u52d8\u574e\u780d\u770b\u4f83\u51f5\u83b0\u83b6\u6221\u9f9b\u77b0",
        "kang": "\u5eb7\u6177\u7ce0\u625b\u6297\u4ea2\u7095\u5751\u4f09\u95f6\u94aa",
        "kao": "\u8003\u62f7\u70e4\u9760\u5c3b\u6832\u7292\u94d0",
        "ken": "\u80af\u5543\u57a6\u6073\u57a0\u88c9\u9880",
        "keng": "\u542d\u5fd0\u94ff",
        "kong": "\u7a7a\u6050\u5b54\u63a7\u5025\u5d06\u7b9c",
        "kou": "\u62a0\u53e3\u6263\u5bc7\u82a4\u853b\u53e9\u770d\u7b58",
        "ku": "\u67af\u54ed\u7a9f\u82e6\u9177\u5e93\u88e4\u5233\u5800\u55be\u7ed4\u9ab7",
        "kua": "\u5938\u57ae\u630e\u8de8\u80ef\u4f89",
        "kuai": "\u5757\u7b77\u4fa9\u5feb\u84af\u90d0\u8489\u72ef\u810d",
        "kuan": "\u5bbd\u6b3e\u9acb",
        "kuang": "\u5321\u7b50\u72c2\u6846\u77ff\u7736\u65f7\u51b5\u8bd3\u8bf3\u909d\u5739\u593c\u54d0\u7ea9\u8d36",
        "kui": "\u4e8f\u76d4\u5cbf\u7aa5\u8475\u594e\u9b41\u5080\u9988\u6127\u6e83\u9997\u532e\u5914\u9697\u63c6\u55b9\u559f\u609d\u6126\u9615\u9035\u668c\u777d\u8069\u8770\u7bd1\u81fe\u8dec",
        "kun": "\u5764\u6606\u6346\u56f0\u6083\u9603\u7428\u951f\u918c\u9cb2\u9ae1",
        "kuo": "\u62ec\u6269\u5ed3\u9614\u86de",
        "la": "\u5783\u62c9\u5587\u8721\u814a\u8fa3\u5566\u524c\u647a\u908b\u65ef\u782c\u760c",
        "lai": "\u83b1\u6765\u8d56\u5d03\u5f95\u6d9e\u6fd1\u8d49\u7750\u94fc\u765e\u7c41",
        "lan": "\u84dd\u5a6a\u680f\u62e6\u7bee\u9611\u5170\u6f9c\u8c30\u63fd\u89c8\u61d2\u7f06\u70c2\u6ee5\u5549\u5c9a\u61d4\u6f24\u6984\u6593\u7f71\u9567\u8934",
        "lang": "\u7405\u6994\u72fc\u5eca\u90ce\u6717\u6d6a\u83a8\u8497\u5577\u9606\u9512\u7a02\u8782",
        "lao": "\u635e\u52b3\u7262\u8001\u4f6c\u59e5\u916a\u70d9\u6d9d\u5520\u5d02\u6833\u94d1\u94f9\u75e8\u91aa",
        "le": "\u52d2\u4e50\u808b\u4ec2\u53fb\u561e\u6cd0\u9cd3",
        "lei": "\u96f7\u956d\u857e\u78ca\u7d2f\u5121\u5792\u64c2\u7c7b\u6cea\u7fb8\u8bd4\u837d\u54a7\u6f2f\u5ad8\u7f27\u6a91\u8012\u9179",
        "ling": "\u68f1\u51b7\u62ce\u73b2\u83f1\u96f6\u9f84\u94c3\u4f36\u7f9a\u51cc\u7075\u9675\u5cad\u9886\u53e6\u4ee4\u9143\u5844\u82d3\u5464\u56f9\u6ce0\u7eeb\u67c3\u68c2\u74f4\u8046\u86c9\u7fce\u9cae",
        "leng": "\u695e\u6123",
        "li": "\u5398\u68a8\u7281\u9ece\u7bf1\u72f8\u79bb\u6f13\u7406\u674e\u91cc\u9ca4\u793c\u8389\u8354\u540f\u6817\u4e3d\u5389\u52b1\u783e\u5386\u5229\u5088\u4f8b\u4fd0\u75e2\u7acb\u7c92\u6ca5\u96b6\u529b\u7483\u54e9\u4fea\u4fda\u90e6\u575c\u82c8\u8385\u84e0\u85dc\u6369\u5456\u5533\u55b1\u7301\u6ea7\u6fa7\u9026\u5a0c\u5ae0\u9a8a\u7f21\u73de\u67a5\u680e\u8f79\u623e\u783a\u8a48\u7f79\u9502\u9e42\u75a0\u75ac\u86ce\u870a\u8821\u7b20\u7be5\u7c9d\u91b4\u8dde\u96f3\u9ca1\u9ce2\u9ee7",
        "lian": "\u4fe9\u8054\u83b2\u8fde\u9570\u5ec9\u601c\u6d9f\u5e18\u655b\u8138\u94fe\u604b\u70bc\u7ec3\u631b\u8539\u5941\u6f4b\u6fc2\u5a08\u740f\u695d\u6b93\u81c1\u81a6\u88e2\u880a\u9ca2",
        "liang": "\u7cae\u51c9\u6881\u7cb1\u826f\u4e24\u8f86\u91cf\u667e\u4eae\u8c05\u589a\u690b\u8e09\u9753\u9b49",
        "liao": "\u64a9\u804a\u50da\u7597\u71ce\u5be5\u8fbd\u6f66\u4e86\u6482\u9563\u5ed6\u6599\u84fc\u5c25\u5639\u7360\u5bee\u7f2d\u948c\u9e69\u8022",
        "lie": "\u5217\u88c2\u70c8\u52a3\u730e\u51bd\u57d2\u6d0c\u8d94\u8e90\u9b23",
        "lin": "\u7433\u6797\u78f7\u9716\u4e34\u90bb\u9cde\u6dcb\u51db\u8d41\u541d\u853a\u5d99\u5eea\u9074\u6aa9\u8f9a\u77b5\u7cbc\u8e8f\u9e9f",
        "liu": "\u6e9c\u7409\u69b4\u786b\u998f\u7559\u5218\u7624\u6d41\u67f3\u516d\u62a1\u507b\u848c\u6cd6\u6d4f\u905b\u9a9d\u7efa\u65d2\u7198\u950d\u954f\u9e68\u938f",
        "long": "\u9f99\u804b\u5499\u7b3c\u7abf\u9686\u5784\u62e2\u9647\u5f04\u5785\u830f\u6cf7\u73d1\u680a\u80e7\u783b\u7643",
        "lou": "\u697c\u5a04\u6402\u7bd3\u6f0f\u964b\u55bd\u5d5d\u9542\u7618\u8027\u877c\u9ac5",
        "lu": "\u82a6\u5362\u9885\u5e90\u7089\u63b3\u5364\u864f\u9c81\u9e93\u788c\u9732\u8def\u8d42\u9e7f\u6f5e\u7984\u5f55\u9646\u622e\u5786\u6445\u64b8\u565c\u6cf8\u6e0c\u6f09\u7490\u680c\u6a79\u8f73\u8f82\u8f98\u6c07\u80ea\u9565\u9e2c\u9e6d\u7c0f\u823b\u9c88",
        "lv": "\u9a74\u5415\u94dd\u4fa3\u65c5\u5c65\u5c61\u7f15\u8651\u6c2f\u5f8b\u7387\u6ee4\u7eff\u634b\u95fe\u6988\u8182\u7a06\u891b",
        "luan": "\u5ce6\u5b6a\u6ee6\u5375\u4e71\u683e\u9e3e\u92ae",
        "lue": "\u63a0\u7565\u950a",
        "lun": "\u8f6e\u4f26\u4ed1\u6ca6\u7eb6\u8bba\u56f5",
        "luo": "\u841d\u87ba\u7f57\u903b\u9523\u7ba9\u9aa1\u88f8\u843d\u6d1b\u9a86\u7edc\u502e\u8366\u645e\u7321\u6cfa\u6924\u8136\u9559\u7630\u96d2",
        "ma": "\u5988\u9ebb\u739b\u7801\u8682\u9a6c\u9a82\u561b\u5417\u551b\u72b8\u5b37\u6769\u9ebd",
        "mai": "\u57cb\u4e70\u9ea6\u5356\u8fc8\u8109\u52a2\u836c\u54aa\u973e",
        "man": "\u7792\u9992\u86ee\u6ee1\u8513\u66fc\u6162\u6f2b\u8c29\u5881\u5e54\u7f26\u71b3\u9558\u989f\u87a8\u9cd7\u9794",
        "mang": "\u8292\u832b\u76f2\u5fd9\u83bd\u9099\u6f2d\u6726\u786d\u87d2",
        "meng": "\u6c13\u840c\u8499\u6aac\u76df\u9530\u731b\u68a6\u5b5f\u52d0\u750d\u77a2\u61f5\u791e\u867b\u8722\u8813\u824b\u8268\u9efe",
        "miao": "\u732b\u82d7\u63cf\u7784\u85d0\u79d2\u6e3a\u5e99\u5999\u55b5\u9088\u7f08\u7f2a\u676a\u6dfc\u7707\u9e4b\u8731",
        "mao": "\u8305\u951a\u6bdb\u77db\u94c6\u536f\u8302\u5192\u5e3d\u8c8c\u8d38\u4f94\u88a4\u52d6\u8306\u5cc1\u7441\u6634\u7266\u8004\u65c4\u61cb\u7780\u86d1\u8765\u87ca\u9ae6",
        "me": "\u4e48",
        "mei": "\u73ab\u679a\u6885\u9176\u9709\u7164\u6ca1\u7709\u5a92\u9541\u6bcf\u7f8e\u6627\u5bd0\u59b9\u5a9a\u5776\u8393\u5d4b\u7338\u6d7c\u6e44\u6963\u9545\u9e5b\u8882\u9b45",
        "men": "\u95e8\u95f7\u4eec\u626a\u739f\u7116\u61d1\u9494",
        "mi": "\u772f\u919a\u9761\u7cdc\u8ff7\u8c1c\u5f25\u7c73\u79d8\u89c5\u6ccc\u871c\u5bc6\u5e42\u8288\u5196\u8c27\u863c\u5627\u7315\u736f\u6c68\u5b93\u5f2d\u8112\u6549\u7cf8\u7e3b\u9e8b",
        "mian": "\u68c9\u7720\u7ef5\u5195\u514d\u52c9\u5a29\u7f05\u9762\u6c94\u6e4e\u817c\u7704",
        "mie": "\u8511\u706d\u54a9\u881b\u7bfe",
        "min": "\u6c11\u62bf\u76bf\u654f\u60af\u95fd\u82e0\u5cb7\u95f5\u6cef\u73c9",
        "ming": "\u660e\u879f\u9e23\u94ed\u540d\u547d\u51a5\u8317\u6e9f\u669d\u7791\u9169",
        "miu": "\u8c2c",
        "mo": "\u6478\u6479\u8611\u6a21\u819c\u78e8\u6469\u9b54\u62b9\u672b\u83ab\u58a8\u9ed8\u6cab\u6f20\u5bde\u964c\u8c1f\u8309\u84e6\u998d\u5aeb\u9546\u79e3\u763c\u8031\u87c6\u8c8a\u8c98",
        "mou": "\u8c0b\u725f\u67d0\u53b6\u54de\u5a7a\u7738\u936a",
        "mu": "\u62c7\u7261\u4ea9\u59c6\u6bcd\u5893\u66ae\u5e55\u52df\u6155\u6728\u76ee\u7766\u7267\u7a46\u4eeb\u82dc\u5452\u6c90\u6bea\u94bc",
        "na": "\u62ff\u54ea\u5450\u94a0\u90a3\u5a1c\u7eb3\u5185\u637a\u80ad\u954e\u8872\u7bac",
        "nai": "\u6c16\u4e43\u5976\u8010\u5948\u9f10\u827f\u8418\u67f0",
        "nan": "\u5357\u7537\u96be\u56ca\u5583\u56e1\u6960\u8169\u877b\u8d67",
        "nao": "\u6320\u8111\u607c\u95f9\u5b6c\u57b4\u7331\u7459\u7847\u94d9\u86f2",
        "ne": "\u6dd6\u5462\u8bb7",
        "nei": "\u9981",
        "nen": "\u5ae9\u80fd\u6798\u6041",
        "ni": "\u59ae\u9713\u502a\u6ce5\u5c3c\u62df\u4f60\u533f\u817b\u9006\u6eba\u4f32\u576d\u730a\u6029\u6ee0\u6635\u65ce\u7962\u615d\u7768\u94cc\u9cb5",
        "nian": "\u852b\u62c8\u5e74\u78be\u64b5\u637b\u5ff5\u5eff\u8f87\u9ecf\u9c87\u9cb6",
        "niang": "\u5a18\u917f",
        "niao": "\u9e1f\u5c3f\u8311\u5b32\u8132\u8885",
        "nie": "\u634f\u8042\u5b7d\u556e\u954a\u954d\u6d85\u4e5c\u9667\u8616\u55eb\u8080\u989e\u81ec\u8e51",
        "nin": "\u60a8\u67e0",
        "ning": "\u72de\u51dd\u5b81\u62e7\u6cde\u4f5e\u84e5\u549b\u752f\u804d",
        "niu": "\u725b\u626d\u94ae\u7ebd\u72c3\u5ff8\u599e\u86b4",
        "nong": "\u8113\u6d53\u519c\u4fac",
        "nu": "\u5974\u52aa\u6012\u5476\u5e11\u5f29\u80ec\u5b65\u9a7d",
        "nv": "\u5973\u6067\u9495\u8844",
        "nuan": "\u6696",
        "nuenue": "\u8650",
        "nue": "\u759f\u8c11",
        "nuo": "\u632a\u61e6\u7cef\u8bfa\u50a9\u6426\u558f\u9518",
        "ou": "\u54e6\u6b27\u9e25\u6bb4\u85d5\u5455\u5076\u6ca4\u6004\u74ef\u8026",
        "pa": "\u556a\u8db4\u722c\u5e15\u6015\u7436\u8469\u7b62",
        "pai": "\u62cd\u6392\u724c\u5f98\u6e43\u6d3e\u4ff3\u848e",
        "pan": "\u6500\u6f58\u76d8\u78d0\u76fc\u7554\u5224\u53db\u723f\u6cee\u88a2\u897b\u87e0\u8e52",
        "pang": "\u4e53\u5e9e\u65c1\u802a\u80d6\u6ec2\u9004",
        "pao": "\u629b\u5486\u5228\u70ae\u888d\u8dd1\u6ce1\u530f\u72cd\u5e96\u812c\u75b1",
        "pei": "\u5478\u80da\u57f9\u88f4\u8d54\u966a\u914d\u4f69\u6c9b\u638a\u8f94\u5e14\u6de0\u65c6\u952b\u9185\u9708",
        "pen": "\u55b7\u76c6\u6e53",
        "peng": "\u7830\u62a8\u70f9\u6f8e\u5f6d\u84ec\u68da\u787c\u7bf7\u81a8\u670b\u9e4f\u6367\u78b0\u576f\u580b\u562d\u6026\u87db",
        "pi": "\u7812\u9739\u6279\u62ab\u5288\u7435\u6bd7\u5564\u813e\u75b2\u76ae\u5339\u75de\u50fb\u5c41\u8b6c\u4e15\u9674\u90b3\u90eb\u572e\u9f19\u64d7\u567c\u5e80\u5ab2\u7eb0\u6787\u7513\u7765\u7f74\u94cd\u75e6\u7656\u758b\u868d\u8c94",
        "pian": "\u7bc7\u504f\u7247\u9a97\u8c1d\u9a88\u728f\u80fc\u890a\u7fe9\u8e41",
        "piao": "\u98d8\u6f02\u74e2\u7968\u527d\u560c\u5ad6\u7f25\u6b8d\u779f\u87b5",
        "pie": "\u6487\u77a5\u4e3f\u82e4\u6c15",
        "pin": "\u62fc\u9891\u8d2b\u54c1\u8058\u62da\u59d8\u5ad4\u6980\u725d\u98a6",
        "ping": "\u4e52\u576a\u82f9\u840d\u5e73\u51ed\u74f6\u8bc4\u5c4f\u4fdc\u5a09\u67b0\u9c86",
        "po": "\u5761\u6cfc\u9887\u5a46\u7834\u9b44\u8feb\u7c95\u53f5\u9131\u6ea5\u73c0\u948b\u94b7\u76a4\u7b38",
        "pou": "\u5256\u88d2\u8e23",
        "pu": "\u6251\u94fa\u4ec6\u8386\u8461\u83e9\u84b2\u57d4\u6734\u5703\u666e\u6d66\u8c31\u66dd\u7011\u530d\u5657\u6fee\u749e\u6c06\u9564\u9568\u8e7c",
        "qi": "\u671f\u6b3a\u6816\u621a\u59bb\u4e03\u51c4\u6f06\u67d2\u6c8f\u5176\u68cb\u5947\u6b67\u7566\u5d0e\u8110\u9f50\u65d7\u7948\u7941\u9a91\u8d77\u5c82\u4e5e\u4f01\u542f\u5951\u780c\u5668\u6c14\u8fc4\u5f03\u6c7d\u6ce3\u8bab\u4e9f\u4e93\u573b\u8291\u840b\u847a\u5601\u5c7a\u5c90\u6c54\u6dc7\u9a90\u7eee\u742a\u7426\u675e\u6864\u69ed\u6b39\u797a\u61a9\u789b\u86f4\u871e\u7da6\u7dae\u8dbf\u8e4a\u9ccd\u9e92",
        "qia": "\u6390\u6070\u6d3d\u845c",
        "qian": "\u7275\u6266\u948e\u94c5\u5343\u8fc1\u7b7e\u4edf\u8c26\u4e7e\u9ed4\u94b1\u94b3\u524d\u6f5c\u9063\u6d45\u8c34\u5811\u5d4c\u6b20\u6b49\u4f65\u9621\u828a\u82a1\u8368\u63ae\u5c8d\u60ad\u614a\u9a9e\u6434\u8930\u7f31\u6920\u80b7\u6106\u94a4\u8654\u7b9d",
        "qiang": "\u67aa\u545b\u8154\u7f8c\u5899\u8537\u5f3a\u62a2\u5af1\u6a2f\u6217\u709d\u9516\u9535\u956a\u8941\u8723\u7f9f\u8deb\u8dc4",
        "qiao": "\u6a47\u9539\u6572\u6084\u6865\u77a7\u4e54\u4fa8\u5de7\u9798\u64ac\u7fd8\u5ced\u4fcf\u7a8d\u5281\u8bee\u8c2f\u835e\u6100\u6194\u7f32\u6a35\u6bf3\u7857\u8df7\u9792",
        "qie": "\u5207\u8304\u4e14\u602f\u7a83\u90c4\u553c\u60ec\u59be\u6308\u9532\u7ba7",
        "qin": "\u94a6\u4fb5\u4eb2\u79e6\u7434\u52e4\u82b9\u64d2\u79bd\u5bdd\u6c81\u82a9\u84c1\u8572\u63ff\u5423\u55ea\u5659\u6eb1\u6a8e\u8793\u887e",
        "qing": "\u9752\u8f7b\u6c22\u503e\u537f\u6e05\u64ce\u6674\u6c30\u60c5\u9877\u8bf7\u5e86\u5029\u82d8\u570a\u6aa0\u78ec\u873b\u7f44\u7b90\u8b26\u9cad\u9ee5",
        "qiong": "\u743c\u7a77\u909b\u8315\u7a79\u7b47\u928e",
        "qiu": "\u79cb\u4e18\u90b1\u7403\u6c42\u56da\u914b\u6cc5\u4fc5\u6c3d\u5def\u827d\u72b0\u6e6b\u9011\u9052\u6978\u8d47\u9e20\u866c\u86af\u8764\u88d8\u7cd7\u9cc5\u9f3d",
        "qu": "\u8d8b\u533a\u86c6\u66f2\u8eaf\u5c48\u9a71\u6e20\u53d6\u5a36\u9f8b\u8da3\u53bb\u8bce\u52ac\u8556\u8627\u5c96\u8862\u9612\u74a9\u89d1\u6c0d\u795b\u78f2\u766f\u86d0\u883c\u9eb4\u77bf\u9ee2",
        "quan": "\u5708\u98a7\u6743\u919b\u6cc9\u5168\u75ca\u62f3\u72ac\u5238\u529d\u8be0\u8343\u737e\u609b\u7efb\u8f81\u754e\u94e8\u8737\u7b4c\u9b08",
        "que": "\u7f3a\u7094\u7638\u5374\u9e4a\u69b7\u786e\u96c0\u9619\u60ab",
        "qun": "\u88d9\u7fa4\u9021",
        "ran": "\u7136\u71c3\u5189\u67d3\u82d2\u9aef",
        "rang": "\u74e4\u58e4\u6518\u56b7\u8ba9\u79b3\u7a70",
        "rao": "\u9976\u6270\u7ed5\u835b\u5a06\u6861",
        "ruo": "\u60f9\u82e5\u5f31",
        "re": "\u70ed\u504c",
        "ren": "\u58ec\u4ec1\u4eba\u5fcd\u97e7\u4efb\u8ba4\u5203\u598a\u7eab\u4ede\u834f\u845a\u996a\u8f6b\u7a14\u887d",
        "reng": "\u6254\u4ecd",
        "ri": "\u65e5",
        "rong": "\u620e\u8338\u84c9\u8363\u878d\u7194\u6eb6\u5bb9\u7ed2\u5197\u5d58\u72e8\u7f1b\u6995\u877e",
        "rou": "\u63c9\u67d4\u8089\u7cc5\u8e42\u97a3",
        "ru": "\u8339\u8815\u5112\u5b7a\u5982\u8fb1\u4e73\u6c5d\u5165\u8925\u84d0\u85b7\u5685\u6d33\u6ebd\u6fe1\u94f7\u8966\u98a5",
        "ruan": "\u8f6f\u962e\u670a",
        "rui": "\u854a\u745e\u9510\u82ae\u8564\u777f\u868b",
        "run": "\u95f0\u6da6",
        "sa": "\u6492\u6d12\u8428\u5345\u4ee8\u6332\u98d2",
        "sai": "\u816e\u9cc3\u585e\u8d5b\u567b",
        "san": "\u4e09\u53c1\u4f1e\u6563\u5f61\u9993\u6c35\u6bf5\u7cc1\u9730",
        "sang": "\u6851\u55d3\u4e27\u6421\u78c9\u98a1",
        "sao": "\u6414\u9a9a\u626b\u5ac2\u57fd\u81ca\u7619\u9ccb",
        "se": "\u745f\u8272\u6da9\u556c\u94e9\u94ef\u7a51",
        "sen": "\u68ee",
        "seng": "\u50e7",
        "sha": "\u838e\u7802\u6740\u5239\u6c99\u7eb1\u50bb\u5565\u715e\u810e\u6b43\u75e7\u88df\u970e\u9ca8",
        "shai": "\u7b5b\u6652\u917e",
        "shan": "\u73ca\u82eb\u6749\u5c71\u5220\u717d\u886b\u95ea\u9655\u64c5\u8d61\u81b3\u5584\u6c55\u6247\u7f2e\u5261\u8baa\u912f\u57cf\u829f\u6f78\u59d7\u9a9f\u81bb\u9490\u759d\u87ee\u8222\u8dda\u9cdd",
        "shang": "\u5892\u4f24\u5546\u8d4f\u664c\u4e0a\u5c1a\u88f3\u57a7\u7ef1\u6b87\u71b5\u89de",
        "shao": "\u68a2\u634e\u7a0d\u70e7\u828d\u52fa\u97f6\u5c11\u54e8\u90b5\u7ecd\u52ad\u82d5\u6f72\u86f8\u7b24\u7b72\u8244",
        "she": "\u5962\u8d4a\u86c7\u820c\u820d\u8d66\u6444\u5c04\u6151\u6d89\u793e\u8bbe\u538d\u4f58\u731e\u7572\u9e9d",
        "shen": "\u7837\u7533\u547b\u4f38\u8eab\u6df1\u5a20\u7ec5\u795e\u6c88\u5ba1\u5a76\u751a\u80be\u614e\u6e17\u8bdc\u8c02\u5432\u54c2\u6e16\u6939\u77e7\u8703",
        "sheng": "\u58f0\u751f\u7525\u7272\u5347\u7ef3\u7701\u76db\u5269\u80dc\u5723\u4e1e\u6e11\u5ab5\u771a\u7b19",
        "shi": "\u5e08\u5931\u72ee\u65bd\u6e7f\u8bd7\u5c38\u8671\u5341\u77f3\u62fe\u65f6\u4ec0\u98df\u8680\u5b9e\u8bc6\u53f2\u77e2\u4f7f\u5c4e\u9a76\u59cb\u5f0f\u793a\u58eb\u4e16\u67ff\u4e8b\u62ed\u8a93\u901d\u52bf\u662f\u55dc\u566c\u9002\u4ed5\u4f8d\u91ca\u9970\u6c0f\u5e02\u6043\u5ba4\u89c6\u8bd5\u8c25\u57d8\u83b3\u84cd\u5f11\u5511\u9963\u8f7c\u8006\u8d33\u70bb\u793b\u94c8\u94ca\u87ab\u8210\u7b6e\u8c55\u9ca5\u9cba",
        "shou": "\u6536\u624b\u9996\u5b88\u5bff\u6388\u552e\u53d7\u7626\u517d\u624c\u72e9\u7ef6\u824f",
        "shu": "\u852c\u67a2\u68b3\u6b8a\u6292\u8f93\u53d4\u8212\u6dd1\u758f\u4e66\u8d4e\u5b70\u719f\u85af\u6691\u66d9\u7f72\u8700\u9ecd\u9f20\u5c5e\u672f\u8ff0\u6811\u675f\u620d\u7ad6\u5885\u5eb6\u6570\u6f31\u6055\u500f\u587e\u83fd\u5fc4\u6cad\u6d91\u6f8d\u59dd\u7ebe\u6bf9\u8167\u6bb3\u956f\u79eb\u9e6c",
        "shua": "\u5237\u800d\u5530\u6dae",
        "shuai": "\u6454\u8870\u7529\u5e05\u87c0",
        "shuan": "\u6813\u62f4\u95e9",
        "shuang": "\u971c\u53cc\u723d\u5b40",
        "shui": "\u8c01\u6c34\u7761\u7a0e",
        "shun": "\u542e\u77ac\u987a\u821c\u6042",
        "shuo": "\u8bf4\u7855\u6714\u70c1\u84b4\u6420\u55cd\u6fef\u5981\u69ca\u94c4",
        "si": "\u65af\u6495\u5636\u601d\u79c1\u53f8\u4e1d\u6b7b\u8086\u5bfa\u55e3\u56db\u4f3a\u4f3c\u9972\u5df3\u53ae\u4fdf\u5155\u83e5\u549d\u6c5c\u6cd7\u6f8c\u59d2\u9a77\u7f0c\u7940\u7960\u9536\u9e36\u801c\u86f3\u7b25",
        "song": "\u677e\u8038\u6002\u9882\u9001\u5b8b\u8bbc\u8bf5\u51c7\u83d8\u5d27\u5d69\u5fea\u609a\u6dde\u7ae6",
        "sou": "\u641c\u8258\u64de\u55fd\u53df\u55d6\u55fe\u998a\u6eb2\u98d5\u778d\u953c\u878b",
        "su": "\u82cf\u9165\u4fd7\u7d20\u901f\u7c9f\u50f3\u5851\u6eaf\u5bbf\u8bc9\u8083\u5919\u8c21\u850c\u55c9\u612b\u7c0c\u89eb\u7a23",
        "suan": "\u9178\u849c\u7b97",
        "sui": "\u867d\u968b\u968f\u7ee5\u9ad3\u788e\u5c81\u7a57\u9042\u96a7\u795f\u84d1\u51ab\u8c07\u6fc9\u9083\u71e7\u772d\u7762",
        "sun": "\u5b59\u635f\u7b0b\u836a\u72f2\u98e7\u69ab\u8de3\u96bc",
        "suo": "\u68ad\u5506\u7f29\u7410\u7d22\u9501\u6240\u5522\u55e6\u5a11\u686b\u7743\u7fa7",
        "ta": "\u584c\u4ed6\u5b83\u5979\u5854\u736d\u631e\u8e4b\u8e0f\u95fc\u6ebb\u9062\u69bb\u6c93",
        "tai": "\u80ce\u82d4\u62ac\u53f0\u6cf0\u915e\u592a\u6001\u6c70\u90b0\u85b9\u80bd\u70b1\u949b\u8dc6\u9c90",
        "tan": "\u574d\u644a\u8d2a\u762b\u6ee9\u575b\u6a80\u75f0\u6f6d\u8c2d\u8c08\u5766\u6bef\u8892\u78b3\u63a2\u53f9\u70ad\u90ef\u8548\u6619\u94bd\u952c\u8983",
        "tang": "\u6c64\u5858\u642a\u5802\u68e0\u819b\u5510\u7cd6\u50a5\u9967\u6e8f\u746d\u94f4\u9557\u8025\u8797\u87b3\u7fb0\u91a3",
        "thang": "\u5018\u8eba\u6dcc",
        "theng": "\u8d9f\u70eb",
        "tao": "\u638f\u6d9b\u6ed4\u7ee6\u8404\u6843\u9003\u6dd8\u9676\u8ba8\u5957\u6311\u9f17\u5555\u97ec\u9955",
        "te": "\u7279",
        "teng": "\u85e4\u817e\u75bc\u8a8a\u6ed5",
        "ti": "\u68af\u5254\u8e22\u9511\u63d0\u9898\u8e44\u557c\u4f53\u66ff\u568f\u60d5\u6d95\u5243\u5c49\u8351\u608c\u9016\u7ee8\u7f07\u9e48\u88fc\u918d",
        "tian": "\u5929\u6dfb\u586b\u7530\u751c\u606c\u8214\u8146\u63ad\u5fdd\u9617\u6b84\u754b\u94bf\u86ba",
        "tiao": "\u6761\u8fe2\u773a\u8df3\u4f7b\u7967\u94eb\u7a95\u9f86\u9ca6",
        "tie": "\u8d34\u94c1\u5e16\u841c\u992e",
        "ting": "\u5385\u542c\u70c3\u6c40\u5ef7\u505c\u4ead\u5ead\u633a\u8247\u839b\u8476\u5a77\u6883\u8713\u9706",
        "tong": "\u901a\u6850\u916e\u77b3\u540c\u94dc\u5f64\u7ae5\u6876\u6345\u7b52\u7edf\u75db\u4f5f\u50ee\u4edd\u833c\u55f5\u6078\u6f7c\u783c",
        "tou": "\u5077\u6295\u5934\u900f\u4ea0",
        "tu": "\u51f8\u79c3\u7a81\u56fe\u5f92\u9014\u6d82\u5c60\u571f\u5410\u5154\u580d\u837c\u83df\u948d\u9174",
        "tuan": "\u6e4d\u56e2\u7583",
        "tui": "\u63a8\u9893\u817f\u8715\u892a\u9000\u5fd2\u717a",
        "tun": "\u541e\u5c6f\u81c0\u9968\u66be\u8c5a\u7a80",
        "tuo": "\u62d6\u6258\u8131\u9e35\u9640\u9a6e\u9a7c\u692d\u59a5\u62d3\u553e\u4e47\u4f57\u5768\u5eb9\u6cb1\u67dd\u7823\u7ba8\u8204\u8dce\u9f0d",
        "wa": "\u6316\u54c7\u86d9\u6d3c\u5a03\u74e6\u889c\u4f64\u5a32\u817d",
        "wai": "\u6b6a\u5916",
        "wan": "\u8c4c\u5f2f\u6e7e\u73a9\u987d\u4e38\u70f7\u5b8c\u7897\u633d\u665a\u7696\u60cb\u5b9b\u5a49\u4e07\u8155\u525c\u8284\u82cb\u83c0\u7ea8\u7efe\u742c\u8118\u7579\u873f\u7ba2",
        "wang": "\u6c6a\u738b\u4ea1\u6789\u7f51\u5f80\u65fa\u671b\u5fd8\u5984\u7f54\u5c22\u60d8\u8f8b\u9b4d",
        "wei": "\u5a01\u5dcd\u5fae\u5371\u97e6\u8fdd\u6845\u56f4\u552f\u60df\u4e3a\u6f4d\u7ef4\u82c7\u840e\u59d4\u4f1f\u4f2a\u5c3e\u7eac\u672a\u851a\u5473\u754f\u80c3\u5582\u9b4f\u4f4d\u6e2d\u8c13\u5c09\u6170\u536b\u502d\u504e\u8bff\u9688\u8473\u8587\u5e0f\u5e37\u5d34\u5d6c\u7325\u732c\u95f1\u6ca9\u6d27\u6da0\u9036\u5a13\u73ae\u97ea\u8ece\u709c\u7168\u71a8\u75ff\u8249\u9c94",
        "wen": "\u761f\u6e29\u868a\u6587\u95fb\u7eb9\u543b\u7a33\u7d0a\u95ee\u520e\u6120\u960c\u6c76\u74ba\u97eb\u6b81\u96ef",
        "weng": "\u55e1\u7fc1\u74ee\u84ca\u8579",
        "wo": "\u631d\u8717\u6da1\u7a9d\u6211\u65a1\u5367\u63e1\u6c83\u83b4\u5e44\u6e25\u674c\u809f\u9f8c",
        "wu": "\u5deb\u545c\u94a8\u4e4c\u6c61\u8bec\u5c4b\u65e0\u829c\u68a7\u543e\u5434\u6bcb\u6b66\u4e94\u6342\u5348\u821e\u4f0d\u4fae\u575e\u620a\u96fe\u6664\u7269\u52ff\u52a1\u609f\u8bef\u5140\u4ef5\u9622\u90ac\u572c\u82b4\u5e91\u6003\u5fe4\u6d6f\u5be4\u8fd5\u59a9\u9a9b\u727e\u7110\u9e49\u9e5c\u8708\u92c8\u9f2f",
        "xi": "\u6614\u7199\u6790\u897f\u7852\u77fd\u6670\u563b\u5438\u9521\u727a\u7a00\u606f\u5e0c\u6089\u819d\u5915\u60dc\u7184\u70ef\u6eaa\u6c50\u7280\u6a84\u88ad\u5e2d\u4e60\u5ab3\u559c\u94e3\u6d17\u7cfb\u9699\u620f\u7ec6\u50d6\u516e\u96b0\u90d7\u831c\u8478\u84f0\u595a\u550f\u5f99\u9969\u960b\u6d60\u6dc5\u5c63\u5b09\u73ba\u6a28\u66e6\u89cb\u6b37\u71b9\u798a\u79a7\u94b8\u7699\u7a78\u8725\u87cb\u823e\u7fb2\u7c9e\u7fd5\u91af\u9f37",
        "xia": "\u778e\u867e\u5323\u971e\u8f96\u6687\u5ce1\u4fa0\u72ed\u4e0b\u53a6\u590f\u5413\u6380\u846d\u55c4\u72ce\u9050\u7455\u7856\u7615\u7f45\u9ee0",
        "xian": "\u9528\u5148\u4ed9\u9c9c\u7ea4\u54b8\u8d24\u8854\u8237\u95f2\u6d8e\u5f26\u5acc\u663e\u9669\u73b0\u732e\u53bf\u817a\u9985\u7fa1\u5baa\u9677\u9650\u7ebf\u51bc\u85d3\u5c98\u7303\u66b9\u5a34\u6c19\u7946\u9e47\u75eb\u86ac\u7b45\u7c7c\u9170\u8df9",
        "xiang": "\u76f8\u53a2\u9576\u9999\u7bb1\u8944\u6e58\u4e61\u7fd4\u7965\u8be6\u60f3\u54cd\u4eab\u9879\u5df7\u6a61\u50cf\u5411\u8c61\u8297\u8459\u9977\u5ea0\u9aa7\u7f03\u87d3\u9c9e\u98e8",
        "xiao": "\u8427\u785d\u9704\u524a\u54ee\u56a3\u9500\u6d88\u5bb5\u6dc6\u6653\u5c0f\u5b5d\u6821\u8096\u5578\u7b11\u6548\u54d3\u54bb\u5d24\u6f47\u900d\u9a81\u7ee1\u67ad\u67b5\u7b71\u7bab\u9b48",
        "xie": "\u6954\u4e9b\u6b47\u874e\u978b\u534f\u631f\u643a\u90aa\u659c\u80c1\u8c10\u5199\u68b0\u5378\u87f9\u61c8\u6cc4\u6cfb\u8c22\u5c51\u5055\u4eb5\u52f0\u71ee\u85a4\u64b7\u5ee8\u7023\u9082\u7ec1\u7f2c\u69ad\u698d\u6b59\u8e9e",
        "xin": "\u85aa\u82af\u950c\u6b23\u8f9b\u65b0\u5ffb\u5fc3\u4fe1\u8845\u56df\u99a8\u8398\u6b46\u94fd\u946b",
        "xing": "\u661f\u8165\u7329\u60fa\u5174\u5211\u578b\u5f62\u90a2\u884c\u9192\u5e78\u674f\u6027\u59d3\u9649\u8347\u8365\u64e4\u60bb\u784e",
        "xiong": "\u5144\u51f6\u80f8\u5308\u6c79\u96c4\u718a\u828e",
        "xiu": "\u4f11\u4fee\u7f9e\u673d\u55c5\u9508\u79c0\u8896\u7ee3\u83a0\u5cab\u9990\u5ea5\u9e3a\u8c85\u9af9",
        "xu": "\u589f\u620c\u9700\u865a\u5618\u987b\u5f90\u8bb8\u84c4\u9157\u53d9\u65ed\u5e8f\u755c\u6064\u7d6e\u5a7f\u7eea\u7eed\u8bb4\u8be9\u5729\u84ff\u6035\u6d2b\u6e86\u987c\u6829\u7166\u7809\u76f1\u80e5\u7cc8\u9191",
        "xuan": "\u8f69\u55a7\u5ba3\u60ac\u65cb\u7384\u9009\u7663\u7729\u7eda\u5107\u8c16\u8431\u63ce\u9994\u6ceb\u6d35\u6e32\u6f29\u7487\u6966\u6684\u70ab\u714a\u78b9\u94c9\u955f\u75c3",
        "xue": "\u9774\u859b\u5b66\u7a74\u96ea\u8840\u5671\u6cf6\u9cd5",
        "xun": "\u52cb\u718f\u5faa\u65ec\u8be2\u5bfb\u9a6f\u5de1\u6b89\u6c5b\u8bad\u8baf\u900a\u8fc5\u5dfd\u57d9\u8340\u85b0\u5ccb\u5f87\u6d54\u66db\u7aa8\u91ba\u9c9f",
        "ya": "\u538b\u62bc\u9e26\u9e2d\u5440\u4e2b\u82bd\u7259\u869c\u5d16\u8859\u6daf\u96c5\u54d1\u4e9a\u8bb6\u4f22\u63e0\u5416\u5c88\u8fd3\u5a05\u740a\u6860\u6c29\u7811\u775a\u75d6",
        "yan": "\u7109\u54bd\u9609\u70df\u6df9\u76d0\u4e25\u7814\u8712\u5ca9\u5ef6\u8a00\u989c\u960e\u708e\u6cbf\u5944\u63a9\u773c\u884d\u6f14\u8273\u5830\u71d5\u538c\u781a\u96c1\u5501\u5f66\u7130\u5bb4\u8c1a\u9a8c\u53a3\u9765\u8d5d\u4fe8\u5043\u5156\u8ba0\u8c33\u90fe\u9122\u82ab\u83f8\u5d26\u6079\u95eb\u960f\u6d07\u6e6e\u6edf\u598d\u5ae3\u7430\u664f\u80ed\u814c\u7131\u7f68\u7b75\u917d\u9b47\u990d\u9f39",
        "yang": "\u6b83\u592e\u9e2f\u79e7\u6768\u626c\u4f6f\u75a1\u7f8a\u6d0b\u9633\u6c27\u4ef0\u75d2\u517b\u6837\u6f3e\u5f89\u600f\u6cf1\u7080\u70ca\u6059\u86d8\u9785",
        "yao": "\u9080\u8170\u5996\u7476\u6447\u5c27\u9065\u7a91\u8c23\u59da\u54ac\u8200\u836f\u8981\u8000\u592d\u723b\u5406\u5d3e\u5fad\u7039\u5e7a\u73e7\u6773\u66dc\u80b4\u9e5e\u7a88\u7e47\u9cd0",
        "ye": "\u6930\u564e\u8036\u7237\u91ce\u51b6\u4e5f\u9875\u6396\u4e1a\u53f6\u66f3\u814b\u591c\u6db2\u8c12\u90ba\u63f6\u9980\u6654\u70e8\u94d8",
        "yi": "\u4e00\u58f9\u533b\u63d6\u94f1\u4f9d\u4f0a\u8863\u9890\u5937\u9057\u79fb\u4eea\u80f0\u7591\u6c82\u5b9c\u59e8\u5f5d\u6905\u8681\u501a\u5df2\u4e59\u77e3\u4ee5\u827a\u6291\u6613\u9091\u5c79\u4ebf\u5f79\u81c6\u9038\u8084\u75ab\u4ea6\u88d4\u610f\u6bc5\u5fc6\u4e49\u76ca\u6ea2\u8be3\u8bae\u8c0a\u8bd1\u5f02\u7ffc\u7fcc\u7ece\u5208\u5293\u4f7e\u8bd2\u572a\u572f\u57f8\u61ff\u82e1\u858f\u5f08\u5955\u6339\u5f0b\u5453\u54a6\u54bf\u566b\u5cc4\u5db7\u7317\u9974\u603f\u6021\u6092\u6f2a\u8fe4\u9a7f\u7f22\u6baa\u8d3b\u65d6\u71a0\u9487\u9552\u9571\u75cd\u7617\u7654\u7fca\u8864\u8734\u8223\u7fbf\u7ff3\u914f\u9edf",
        "yin": "\u8335\u836b\u56e0\u6bb7\u97f3\u9634\u59fb\u541f\u94f6\u6deb\u5bc5\u996e\u5c39\u5f15\u9690\u5370\u80e4\u911e\u5819\u831a\u5591\u72fa\u5924\u6c24\u94df\u763e\u8693\u972a\u9f88",
        "ying": "\u82f1\u6a31\u5a74\u9e70\u5e94\u7f28\u83b9\u8424\u8425\u8367\u8747\u8fce\u8d62\u76c8\u5f71\u9896\u786c\u6620\u5b34\u90e2\u8314\u83ba\u8426\u6484\u5624\u81ba\u6ee2\u6f46\u701b\u745b\u748e\u6979\u9e66\u763f\u988d\u7f42",
        "yo": "\u54df\u5537",
        "yong": "\u62e5\u4f63\u81c3\u75c8\u5eb8\u96cd\u8e0a\u86f9\u548f\u6cf3\u6d8c\u6c38\u607f\u52c7\u7528\u4fd1\u58c5\u5889\u6175\u9095\u955b\u752c\u9cd9\u9954",
        "you": "\u5e7d\u4f18\u60a0\u5fe7\u5c24\u7531\u90ae\u94c0\u72b9\u6cb9\u6e38\u9149\u6709\u53cb\u53f3\u4f51\u91c9\u8bf1\u53c8\u5e7c\u5363\u6538\u4f91\u83b8\u5466\u56ff\u5ba5\u67da\u7337\u7256\u94d5\u75a3\u8763\u9c7f\u9edd\u9f2c",
        "yu": "\u8fc2\u6de4\u4e8e\u76c2\u6986\u865e\u611a\u8206\u4f59\u4fde\u903e\u9c7c\u6109\u6e1d\u6e14\u9685\u4e88\u5a31\u96e8\u4e0e\u5c7f\u79b9\u5b87\u8bed\u7fbd\u7389\u57df\u828b\u90c1\u5401\u9047\u55bb\u5cea\u5fa1\u6108\u6b32\u72f1\u80b2\u8a89\u6d74\u5bd3\u88d5\u9884\u8c6b\u9a6d\u79ba\u6bd3\u4f1b\u4fe3\u8c00\u8c15\u8438\u84e3\u63c4\u5581\u5704\u5709\u5d5b\u72f3\u996b\u5ebe\u9608\u59aa\u59a4\u7ea1\u745c\u6631\u89ce\u8174\u6b24\u65bc\u715c\u71e0\u807f\u94b0\u9e46\u7610\u7600\u7ab3\u8753\u7afd\u8201\u96e9\u9f89",
        "yuan": "\u9e33\u6e0a\u51a4\u5143\u57a3\u8881\u539f\u63f4\u8f95\u56ed\u5458\u5706\u733f\u6e90\u7f18\u8fdc\u82d1\u613f\u6028\u9662\u586c\u6c85\u5a9b\u7457\u6a7c\u7230\u7722\u9e22\u8788\u9f0b",
        "yue": "\u66f0\u7ea6\u8d8a\u8dc3\u94a5\u5cb3\u7ca4\u6708\u60a6\u9605\u9fa0\u6a3e\u5216\u94ba",
        "yun": "\u8018\u4e91\u90e7\u5300\u9668\u5141\u8fd0\u8574\u915d\u6655\u97f5\u5b55\u90d3\u82b8\u72c1\u607d\u7ead\u6b92\u6600\u6c32",
        "za": "\u531d\u7838\u6742\u62f6\u5482",
        "zai": "\u683d\u54c9\u707e\u5bb0\u8f7d\u518d\u5728\u54b1\u5d3d\u753e",
        "zan": "\u6512\u6682\u8d5e\u74d2\u661d\u7c2a\u7ccc\u8db1\u933e",
        "zang": "\u8d43\u810f\u846c\u5958\u6215\u81e7",
        "zao": "\u906d\u7cdf\u51ff\u85fb\u67a3\u65e9\u6fa1\u86a4\u8e81\u566a\u9020\u7682\u7076\u71e5\u5523\u7f2b",
        "ze": "\u8d23\u62e9\u5219\u6cfd\u4ec4\u8d5c\u5567\u8fee\u6603\u7b2e\u7ba6\u8234",
        "zei": "\u8d3c",
        "zen": "\u600e\u8c2e",
        "zeng": "\u589e\u618e\u66fe\u8d60\u7f2f\u7511\u7f7e\u9503",
        "zha": "\u624e\u55b3\u6e23\u672d\u8f67\u94e1\u95f8\u7728\u6805\u69a8\u548b\u4e4d\u70b8\u8bc8\u63f8\u5412\u54a4\u54f3\u600d\u781f\u75c4\u86b1\u9f44",
        "zhai": "\u6458\u658b\u5b85\u7a84\u503a\u5be8\u7826",
        "zhan": "\u77bb\u6be1\u8a79\u7c98\u6cbe\u76cf\u65a9\u8f97\u5d2d\u5c55\u8638\u6808\u5360\u6218\u7ad9\u6e5b\u7efd\u8c35\u640c\u65c3",
        "zhang": "\u6a1f\u7ae0\u5f70\u6f33\u5f20\u638c\u6da8\u6756\u4e08\u5e10\u8d26\u4ed7\u80c0\u7634\u969c\u4ec9\u9123\u5e5b\u5d82\u7350\u5adc\u748b\u87d1",
        "zhao": "\u62db\u662d\u627e\u6cbc\u8d75\u7167\u7f69\u5146\u8087\u53ec\u722a\u8bcf\u68f9\u948a\u7b0a",
        "zhe": "\u906e\u6298\u54f2\u86f0\u8f99\u8005\u9517\u8517\u8fd9\u6d59\u8c2a\u966c\u67d8\u8f84\u78d4\u9e67\u891a\u8707\u8d6d",
        "zhen": "\u73cd\u659f\u771f\u7504\u7827\u81fb\u8d1e\u9488\u4fa6\u6795\u75b9\u8bca\u9707\u632f\u9547\u9635\u7f1c\u6862\u699b\u8f78\u8d48\u80d7\u6715\u796f\u755b\u9e29",
        "zheng": "\u84b8\u6323\u7741\u5f81\u72f0\u4e89\u6014\u6574\u62ef\u6b63\u653f\u5e27\u75c7\u90d1\u8bc1\u8be4\u5ce5\u94b2\u94ee\u7b5d",
        "zhi": "\u829d\u679d\u652f\u5431\u8718\u77e5\u80a2\u8102\u6c41\u4e4b\u7ec7\u804c\u76f4\u690d\u6b96\u6267\u503c\u4f84\u5740\u6307\u6b62\u8dbe\u53ea\u65e8\u7eb8\u5fd7\u631a\u63b7\u81f3\u81f4\u7f6e\u5e1c\u5cd9\u5236\u667a\u79e9\u7a1a\u8d28\u7099\u75d4\u6ede\u6cbb\u7a92\u536e\u965f\u90c5\u57f4\u82b7\u646d\u5e19\u5fee\u5f58\u54ab\u9a98\u6809\u67b3\u6800\u684e\u8f75\u8f7e\u6534\u8d3d\u81a3\u7949\u7957\u9ef9\u96c9\u9e37\u75e3\u86ed\u7d77\u916f\u8dd6\u8e2c\u8e2f\u8c78\u89ef",
        "zhong": "\u4e2d\u76c5\u5fe0\u949f\u8877\u7ec8\u79cd\u80bf\u91cd\u4ef2\u4f17\u51a2\u953a\u87bd\u8202\u822f\u8e35",
        "zhou": "\u821f\u5468\u5dde\u6d32\u8bcc\u7ca5\u8f74\u8098\u5e1a\u5492\u76b1\u5b99\u663c\u9aa4\u5544\u7740\u501c\u8bf9\u836e\u9b3b\u7ea3\u80c4\u78a1\u7c40\u8233\u914e\u9cb7",
        "zhu": "\u73e0\u682a\u86db\u6731\u732a\u8bf8\u8bdb\u9010\u7af9\u70db\u716e\u62c4\u77a9\u5631\u4e3b\u8457\u67f1\u52a9\u86c0\u8d2e\u94f8\u7b51\u4f4f\u6ce8\u795d\u9a7b\u4f2b\u4f8f\u90be\u82ce\u8331\u6d19\u6e1a\u6f74\u9a7a\u677c\u69e0\u6a65\u70b7\u94e2\u75b0\u7603\u86b0\u7afa\u7bb8\u7fe5\u8e85\u9e88",
        "zhua": "\u6293",
        "zhuai": "\u62fd",
        "zhuan": "\u4e13\u7816\u8f6c\u64b0\u8d5a\u7bc6\u629f\u556d\u989b",
        "zhuang": "\u6869\u5e84\u88c5\u5986\u649e\u58ee\u72b6\u4e2c",
        "zhui": "\u690e\u9525\u8ffd\u8d58\u5760\u7f00\u8411\u9a93\u7f12",
        "zhun": "\u8c06\u51c6",
        "zhuo": "\u6349\u62d9\u5353\u684c\u7422\u8301\u914c\u707c\u6d4a\u502c\u8bfc\u5ef4\u855e\u64e2\u555c\u6d5e\u6dbf\u6753\u712f\u799a\u65ab",
        "zi": "\u5179\u54a8\u8d44\u59ff\u6ecb\u6dc4\u5b5c\u7d2b\u4ed4\u7c7d\u6ed3\u5b50\u81ea\u6e0d\u5b57\u8c18\u5d6b\u59ca\u5b73\u7f01\u6893\u8f8e\u8d40\u6063\u7726\u9531\u79ed\u8014\u7b2b\u7ca2\u89dc\u8a3e\u9cbb\u9aed",
        "zong": "\u9b03\u68d5\u8e2a\u5b97\u7efc\u603b\u7eb5\u8159\u7cbd",
        "zou": "\u90b9\u8d70\u594f\u63cd\u9139\u9cb0",
        "zu": "\u79df\u8db3\u5352\u65cf\u7956\u8bc5\u963b\u7ec4\u4fce\u83f9\u5550\u5f82\u9a75\u8e74",
        "zuan": "\u94bb\u7e82\u6525\u7f35",
        "zui": "\u5634\u9189\u6700\u7f6a",
        "zun": "\u5c0a\u9075\u6499\u6a3d\u9cdf",
        "zuo": "\u6628\u5de6\u4f50\u67de\u505a\u4f5c\u5750\u5ea7\u961d\u963c\u80d9\u795a\u9162",
        "cou": "\u85ae\u6971\u8f8f\u8160",
        "nang": "\u652e\u54dd\u56d4\u9995\u66e9",
        "o": "\u5594",
        "dia": "\u55f2",
        "chuai": "\u562c\u81aa\u8e39",
        "cen": "\u5c91\u6d94",
        "diu": "\u94e5",
        "nou": "\u8028",
        "fou": "\u7f36",
        "bia": "\u9adf"
    };
    
    // 汉字转拼音
    function ConvertPinyin(l1) {
        var l2 = l1.length;
        var I1 = "";
        var reg = new RegExp('[a-zA-Z0-9\- ]');
        for (var i = 0; i < l2; i++) {
            var val = l1.substr(i, 1);
            var name = arraySearch(val, PinYin);
            if(i==1){
            	I1 += " ";//拼音姓与名加空格
            }
            if (reg.test(val)) {
                I1 += val;
            } else if (name !== false) {
                I1 += name;
            }
    
        }
        I1 = I1.replace(/ /g, '-');
        while (I1.indexOf('--') > 0) {
            I1 = I1.replace('--', '-');
        }
        I1 = I1.replace('-', ' ');
        return I1;
    }
    
    // 在对象中搜索
    function arraySearch(l1, l2) {
        for (var name in PinYin) {
            if (PinYin[name].indexOf(l1) != -1) {
                return uc(name);
                break;
            }
        }
        return false;
    }
    
    // 首字母大写
    function ucfirst(l1) {
        if (l1.length > 0) {
            var first = l1.substr(0, 1).toUpperCase();
            var spare = l1.substr(1, l1.length);
            return first + spare;
            // return first;
        }
    }
    
    
    //大写
    function uc(l1) {
        if (l1.length > 0) {
            var spare = l1.toUpperCase();
          
            return spare;
            // return first;
        }
    }

     

    ----------------------------------------------------------------------------------------------------------------------------------------------------------

    补充:

    以下是从其他项目拷贝来的,没检验具体效果如何

    拼音转汉子:

    pinyin_dict_notone.js 

    收录常用汉字6763个,不支持声调,支持多音字,并按照汉字使用频率由低到高排序
    /**
     * 收录常用汉字6763个,不支持声调,支持多音字,并按照汉字使用频率由低到高排序
     */
    var pinyin_dict_notone = 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    pinyin_dict_withtone.js

    var pinyin_dict_withtone = "yī,dīng zhēng,kǎo qiǎo yú,qī,shàng,xià,hǎn,wàn mò,zhàng,sān,shàng shǎng,xià,qí jī,bù fǒu,yǔ yù yú,miǎn,gài,chǒu,chǒu,zhuān,qiě jū,pī,shì,shì,qiū,bǐng,yè,cóng,dōng,sī,chéng,diū,qiū,liǎng,diū,yǒu,liǎng,yán,bìng,sāng sàng,gǔn,jiū,gè gě,yā,pán,zhōng zhòng,jǐ,jiè,fēng,guàn kuàng,chuàn,chǎn,lín,zhuó,zhǔ,bā,wán,dān,wéi wèi,zhǔ,jǐng,lì lí,jǔ,piě,fú,yí jí,yì,nǎi,wǔ,jiǔ,jiǔ,tuō zhé,me yāo mó ma,yì,yī,zhī,wū,zhà,hū,fá,lè yuè,yín,pīng,pāng,qiáo,hǔ,guāi,chéng shèng,chéng shèng,yǐ,háo yǐ,yǐ,miē niè,jiǔ,qǐ,yě,xí,xiāng,gài,jiǔ,xià,hù,shū,dǒu,shǐ,jī,náng,jiā,none,shí,none,hū,mǎi,luàn,none,rǔ,xué,yǎn,fǔ,shā,nǎ,qián,suǒ,yú,zhù,zhě,qián gān,zhì luàn,guī,qián,luàn,lǐn lìn,yì,jué,le liǎo,gè mā,yú yǔ,zhēng,shì,shì,èr,chù,yú,kuī,yú,yún,hù,qí,wǔ,jǐng,sì,suì,gèn,gèn,yà,xiē suò,yà,qí zhāi,yā yà,jí qì,tóu,wáng wú,kàng,dà,jiāo,hài,yì,chǎn,hēng pēng,mǔ,ye,xiǎng,jīng,tíng,liàng,xiǎng,jīng,yè,qīn qìng,bó,yòu,xiè,dǎn dàn,lián,duǒ,wěi mén,rén,rén,jí,jí,wáng,yì,shén shí,rén,lè,dīng,zè,jǐn jìn,pū pú,chóu qiú,bā,zhǎng,jīn,jiè,bīng,réng,cóng zòng,fó,jīn sǎn,lún,bīng,cāng,zī zǐ zǎi,shì,tā,zhàng,fù,xiān,xiān,tuō chà duó,hóng,tóng,rèn,qiān,gǎn hàn,yì gē,bó,dài,líng lǐng lìng,yǐ,chào,cháng zhǎng,sā,cháng,yí,mù,mén,rèn,fǎn,chào miǎo,yǎng áng,qián,zhòng,pǐ pí,wò,wǔ,jiàn,jià jiè jie,yǎo fó,fēng,cāng,rèn rén,wáng,fèn bīn,dī,fǎng,zhōng,qǐ,pèi,yú,diào,dùn,wěn,yì,xǐn,kàng,yī,jí,ài,wǔ,jì qí,fú,fá,xiū xǔ,jìn yín,pī,dǎn,fū,tǎng,zhòng,yōu,huǒ,huì kuài,yǔ,cuì,yún,sǎn,wěi,chuán zhuàn,chē jū,yá,qiàn,shāng,chāng,lún,cāng chen,xùn,xìn,wěi,zhù,chǐ,xián xuán,nú nǔ,bó bǎi bà,gū gù,nǐ,nǐ nì,xiè,bàn,xù,líng,zhòu,shēn,qū,sì cì,bēng,sì shì,qié jiā gā,pī,yì,sì,yǐ chì,zhēng,diàn tián,hān gàn,mài,dàn,zhù,bù,qū,bǐ,zhāo shào,cǐ,wèi,dī,zhù,zuǒ,yòu,yǎng,tǐ tī bèn,zhàn diān,hé hē hè,bì,tuó,shé,yú,yì dié,fó fú bì bó,zuò,gōu kòu,nìng,tóng,nǐ,xiān,qú,yōng yòng,wǎ,qiān,yòu,kǎ,bāo,pèi,huí huái,gé,lǎo,xiáng,gé,yáng,bǎi,fǎ,mǐng,jiā,èr nài,bìng,jí,hěn,huó,guǐ,quán,tiāo,jiǎo,cì,yì,shǐ,xíng,shēn,tuō,kǎn,zhí,gāi,lái,yí,chǐ,kuǎ,gōng,lì,yīn,shì,mǐ,zhū,xù,yòu,ān,lù,móu,ér,lún,dòng tóng tǒng,chà,chì,xùn,gōng gòng,zhōu,yī,rú,cún jiàn,xiá,sì,dài,lǚ,ta,jiǎo yáo,zhēn,cè zè zhāi,qiáo,kuài,chái,nìng,nóng,jǐn,wǔ,hóu hòu,jiǒng,chěng tǐng,zhèn zhēn,zuò,hào,qīn,lǚ,jú,shù dōu,tǐng,shèn,tuó tuì,bó,nán,xiāo,biàn pián,tuǐ,yǔ,xì,cù,é,qiú,xú,guàng,kù,wù,jùn,yì,fǔ,liáng,zǔ,qiào xiào,lì,yǒng,hùn,jìng,qiàn,sàn,pěi,sú,fú,xī,lǐ,fǔ,pīng,bǎo,yú yù shù,sì qí,xiá,xìn shēn,xiū,yǔ,dì,chē jū,chóu,zhì,yǎn,liǎ,lì,lái,sī,jiǎn,xiū,fǔ,huò,jù,xiào,pái,jiàn,biào,chù tì,fèi,fèng,yà,ǎn,bèi,yù,xīn,bǐ,hǔ chí,chāng,zhī,bìng,jiù,yáo,cuì zú,liǎ,wǎn,lái,cāng,zǒng,gè gě,guān,bèi,tiǎn,shū,shū,mén,dǎo dào,tán tàn,jué juè,chuí,xìng,péng,tǎng cháng,hòu,yǐ,qī,tì,gàn,liàng jìng,jiè,suī,chàng chāng,jié,fǎng,zhí,kōng kǒng,juàn,zōng,jù,qiàn,ní,lún,zhuō,wō wēi,luǒ,sōng,lèng,hùn,dōng,zì,bèn,wǔ,jù,nǎi,cǎi,jiǎn,zhài,yē,zhí,shà,qīng,nìng,yīng,chēng chèn,qián,yǎn,ruǎn,zhòng tóng,chǔn,jiǎ jià,jì jié,wěi,yú,bǐng bìng,ruò,tí,wēi,piān,yàn,fēng,tǎng dàng,wò,è,xié,chě,shěng,kǎn,dì,zuò,chā,tíng,bèi,xiè,huáng,yǎo,zhàn,chǒu qiào,ān,yóu,jiàn,xū,zhā,cī,fù,bī,zhì,zǒng,miǎn,jí,yǐ,xiè,xún,cāi sī,duān,cè zè zhāi,zhēn,ǒu,tōu,tōu,bèi,zá zǎ,lǚ lóu,jié,wěi,fèn,cháng,kuǐ guī,sǒu,zhì sī,sù,xiā,fù,yuàn yuán,rǒng,lì,nù,yùn,jiǎng gòu,mà,bàng,diān,táng,hào,jié,xī xì,shān,qiàn jiān,què jué,cāng chen,chù,sǎn,bèi,xiào,róng,yáo,tà tàn,suō,yǎng,fá,bìng,jiā,dǎi,zài,tǎng,gǔ,bīn,chǔ,nuó,cān càn,lěi,cuī,yōng,zāo cáo,zǒng,péng,sǒng,ào,chuán zhuàn,yǔ,zhài,qī còu,shāng,chuǎng,jìng,chì,shǎ,hàn,zhāng,qīng,yān yàn,dì,xiè,lǚ lóu,bèi,piào biāo,jǐn jìn,liàn,lù,màn,qiān,xiān,tǎn tàn,yíng,dòng,zhuàn,xiàng,shàn,qiáo,jiǒng,tuǐ tuí,zǔn,pú,xī,láo,chǎng,guāng,liáo,qī,chēng dēng,zhàn zhuàn chán,wěi,jī,bō,huì,chuǎn,tiě jiàn,dàn,jiǎo yáo,jiù,sēng,fèn,xiàn,yù jú,è wù wū,jiāo,jiàn,tóng zhuàng,lǐn,bó,gù,xiān,sù,xiàn,jiāng,mǐn,yè,jìn,jià jie,qiào,pì,fēng,zhòu,ài,sài,yí,jùn,nóng,chán tǎn shàn,yì,dāng dàng,jǐng,xuān,kuài,jiǎn,chù,dān dàn,jiǎo,shǎ,zài,càn,bīn bìn,án àn,rú,tái,chóu,chái,lán,nǐ yì,jǐn,qiàn,méng,wǔ,níng,qióng,nǐ,cháng,liè,lěi,lǚ,kuǎng,bào,yù,biāo,zǎn,zhì,sì,yōu,háo,qìng,chèn,lì,téng,wěi,lǒng lóng lòng,chǔ,chán chàn,ráng xiāng,shū,huì xié,lì,luó,zǎn,nuó,tǎng,yǎn,léi,nàng nāng,ér,wù,yǔn,zān,yuán,xiōng,chōng,zhào,xiōng,xiān,guāng,duì ruì yuè,kè,duì ruì yuè,miǎn,tù,cháng zhǎng,ér,duì ruì yuè,ér,qīn,tù,sì,yǎn,yǎn,shǐ,shí kè,dǎng,qiān,dōu,fēn,máo,shēn,dōu,bǎi kè,jīng,lǐ,huǎng,rù,wáng,nèi,quán,liǎng,yú shù,bā,gōng,liù lù,xī,han,lán,gòng gōng,tiān,guān,xīng xìng,bīng,qí jī,jù,diǎn,zī cí,fēn,yǎng,jiān,shòu,jì,yì,jì,chǎn,jiōng,mào,rǎn,nèi nà,yuán,mǎo,gāng,rǎn,cè,jiōng,cè,zài,guǎ,jiǒng,mào,zhòu,mào mò,gòu,xú,miǎn,mì,rǒng,yín yóu,xiě,kǎn,jūn,nóng,yí,mí,shì,guān guàn,měng,zhǒng,zuì,yuān,míng,kòu,lín,fù,xiě,mì,bīng,dōng,tài,gāng,féng píng,bīng,hù,chōng chòng,jué,yà,kuàng,yě,lěng,pàn,fā,mǐn,dòng,xiǎn,liè,qià,jiān,jìng chēng,sōu,měi,tú,qī,gù,zhǔn,sōng,jìng chēng,liáng liàng,qìng,diāo,líng,dòng,gàn,jiǎn,yīn,còu,ái,lì,cāng,mǐng,zhǔn,cuī,sī,duó,jìn,lǐn,lǐn,níng,xī,dú,jī jǐ,fán,fán,fán,fèng,jū,chù chǔ,zhēng,fēng,mù,zhǐ,fú,fēng,píng,fēng,kǎi,huáng,kǎi,gān,dèng,píng,kǎn qiǎn,xiōng,kuài,tū,āo wā,chū,jī,dàng,hán,hán,záo,dāo,diāo,dāo,rèn,rèn,chuāng,fēn fèn,qiē qiè,yì,jī,kān,qiàn,cǔn,chú,wěn,jī,dǎn,xíng,huá huà,wán,jué,lí,yuè,liè,liú,zé,gāng,chuàng chuāng,fú,chū,qù,diāo,shān,mǐn,líng,zhōng,pàn,bié biè,jié,jié,páo bào,lì,shān,bié biè,chǎn chàn,jǐng,guā,gēng,dào,chuàng,kuī,kū,duò,èr,zhì,shuā shuà,quàn xuàn,chà shā,cì cī,kè,jié,guì,cì,guì,kǎi,duò,jì,tì,jǐng,dōu,luǒ,zé,yuān,cuò,xiāo xuē,kēi kè,là lá,qián,chà shā,chuàng,guǎ,jiàn,cuò,lí,tī,fèi,pōu,chǎn chàn,qí,chuàng,zì,gāng,wān,bāo bō,jī,duō,qíng,yǎn shàn,dū zhuó,jiàn,jì,bāo bō,yān,jù,huò,shèng,jiǎn,duó,zhì duān,wū,guǎ,fù pì,shèng,jiàn,gē,dá zhá,kǎi,chuàng chuāng,chuán,chǎn,tuán zhuān,lù jiū,lí,pēng,shān,piāo,kōu,jiǎo chāo,guā,qiāo,jué,huá huà,zhā zhá,zhuó,lián,jù,pī pǐ,liú,guì,jiǎo chāo,guì,jiàn,jiàn,tāng,huō,jì,jiàn,yì,jiàn,zhì,chán,zuān,mó,lí,zhú,lì,yà,quàn,bàn,gōng,jiā,wù,mài,liè,jìn jìng,kēng,xié liè,zhǐ,dòng,zhù chú,nǔ,jié,qú,shào,yì,zhǔ,miǎo,lì,jìn jìng,láo,láo,juàn,kǒu,yáng,wā,xiào,móu,kuāng,jié,liè,hé,shì,kè,jìn jìng,gào,bó bèi,mǐn,chì,láng,yǒng,yǒng,miǎn,kè,xūn,juàn juān,qíng,lù,bù,měng,chì,lè lēi,kài,miǎn,dòng,xù,xù,kān,wù,yì,xūn,wěng yǎng,shèng,láo,mù,lù,piāo,shì,jì,qín,jiàng,jiǎo chāo,quàn,xiàng,yì,qiāo,fān,juān,tóng dòng,jù,dān,xié,mài,xūn,xūn,lǜ,lì,chè,ráng xiāng,quàn,bāo,sháo,yún,jiū,bào,gōu gòu,wù,yún,none,xiōng,gài,gài,bāo,cōng,yì,xiōng,pēng,jū,táo yáo,gé,pú,è,páo,fú,gōng,dá,jiù,gōng,bǐ,huà huā,běi bèi,nǎo,chí shi,fāng,jiù,yí,zā,jiàng,kàng,jiàng,kuāng,hū,xiá,qū,fán,guǐ,qiè,zāng cáng,kuāng,fěi,hū,yǔ,guǐ,kuì guì,huì,dān,kuì guì,lián,lián,suǎn,dú,jiù,jué,xì,pǐ,qū ōu,yī,kē qià,yǎn yàn,biǎn,nì,qū ōu,shí,xùn,qiān,niàn,sà,zú,shēng,wǔ,huì,bàn,shì,xì,wàn,huá huà huā,xié,wàn,bēi,zú cù,zhuó,xié,dān shàn chán,mài,nán nā,dān,jí,bó,shuài lǜ,bǔ bo,guàn kuàng,biàn,bǔ,zhān zhàn,qiǎ kǎ,lú,yǒu,lǔ,xī,guà,wò,xiè,jié,jié,wèi,yǎng áng,qióng,zhī,mǎo,yìn,wēi,shào,jí,què,luǎn,chǐ,juàn juǎn,xiè,xù,jǐn,què,wù,jí,è,qīng,xī,sān,chǎng ān hàn,wēi yán,è,tīng,lì,zhé zhái,hàn àn,lì,yǎ,yā yà,yàn,shè,dǐ,zhǎ zhǎi,páng,none,qiè,yá,zhì shī,cè,máng,tí,lí,shè,hòu,tīng,zuī,cuò,fèi,yuán,cè,yuán,xiāng,yǎn,lì,jué,shà xià,diān,chú,jiù,jǐn,áo,guǐ,yàn,sī,lì,chǎng,qiān lán,lì,yán,yǎn,yuán,sī mǒu,gōng hóng,lín miǎo,róu qiú,qù,qù,none,lěi,dū,xiàn xuán,zhuān,sān,cān shēn cēn sān,cān shēn cēn sān,cān shēn cēn sān,cān shēn cēn sān,ài yǐ,dài,yòu,chā chá chǎ,jí,yǒu,shuāng,fǎn,shōu,guái,bá,fā fà,ruò,lì,shū,zhuó yǐ lì jué,qǔ,shòu,biàn,xù,jiǎ,pàn,sǒu,jí,wèi yù,sǒu,dié,ruì,cóng,kǒu,gǔ,jù gōu,lìng,guǎ,tāo dāo,kòu,zhī zhǐ,jiào,zhào shào,bā,dīng,kě kè,tái tāi,chì,shǐ,yòu,qiú,pǒ,yè xié,hào háo,sī,tàn,chǐ,lè,diāo,jī,none,hōng hóng,miē,xū yù,máng,chī,gè gě,xuān sòng,yāo,zǐ,hé gě,jí,diào,dòu cùn,tóng tòng,míng,hòu,lì,tǔ tù,xiàng,zhà zhā,xià hè,yē,lǚ,yā ā,ma má mǎ,ǒu,huō,yī,jūn,chǒu,lìn,tūn,yín,fèi,pǐ bǐ,qìn,qìn,jiè gè,bù,fǒu pǐ,bā ba,dūn,fēn,é huā,hán,tīng,háng kēng,shǔn,qǐ,hóng,zhī zī,yǐn shěn,wú,wú,chǎo chāo,nà nè,xuè chuò jué,xī,chuī,dōu rú,wěn,hǒu,hǒu hōng ōu,wú yù,gào,yā ya,jùn,lǚ,è,gé,wěn,dāi,qǐ,chéng,wú,gào,fū,jiào,hōng,chǐ,shēng,nà nè,tūn tiān,fǔ,yì,dāi,ǒu ōu òu,lì,bei bài,yuán yún yùn,wā guǎ guō,huá qì,qiāng qiàng,wū,è,shī,juǎn,pěn,wěn mǐn,ní ne,m,líng,rán,yōu,dǐ,zhōu,shì,zhòu,tiè chè,xì,yì,qì zhī,píng,zǐ cī,guā gū guǎ,zī cī,wèi,xǔ hǒu gòu,hē a kē,náo,xiā,pēi,yì,xiāo háo,shēn,hū,mìng,dá dàn,qū,jǔ zuǐ,xián gān,zā,tuō,duō,pǒu,páo,bì,fú,yǎng,hé hè,zǎ zé zhā,hé hè huó huò hú,hāi,jiù,yǒng,fù,dā,zhòu,wǎ,kǎ,gū,kā gā,zuo,bù,lóng,dōng,níng,tuō,sī,xiàn xián,huò,qì,èr,è,guāng,zhà,dié xī,yí,liě liē lié lie,zī,miē,mī,zhǐ,yǎo,jī xī qià,zhòu,kǎ luò gē,shù xún,zá zǎ,xiào,ké hāi,huī,kuā,huài shì,táo,xián,è àn,xuǎn xuān,xiū,wā guǎ guō,yān yàn yè,lǎo,yī,āi,pǐn,shěn,tóng,hōng hǒng hòng,xiōng,duō,wā wa,hā hǎ hà,zāi,yòu,diè dì,pài,xiǎng,āi,gén hěn,kuāng,yǎ yā,dā,xiāo,bì,yuě huì,nián,huá huā,xíng,kuài,duǒ,fēn,jì jiē zhāi,nóng,mōu,yō yo,hào,yuán yún yùn,lòng,pǒu,máng,gē,ó ò é,chī,shào,li lǐ lī,nǎ něi na né,zú,hè,kū,xiào,xiàn,láo,pò bā bō,zhé,zhā,liàng láng,bā,miē,liè lǜ,suī,fú,bǔ,hān,hēng,gěng,chuò yuè,gě jiā,yòu,yàn,gū,gū,bei bài,hán hàn,suō,chún,yì,āi ài,jiá qiǎn,tǔ tù,dàn xián yán,wǎn,lì,xī,táng,zuò,qiú,chē,wù wú ń,zào,yǎ,dōu,qǐ,dí,qìn,mà,none,gòng hǒng gǒng,dǒu,none,lào láo,liǎng,suǒ,zào,huàn,léng,shā,jī,zǔ,wō wěi,fěng,jìn yín,hǔ xià,qì,shòu,wéi,shuā,chàng,ér wā,lì,qiàng,ǎn,jiè zé jí,yō,niàn,yū,tiǎn,lài,shà,xī,tuò,hū,ái,zhōu zhāo tiào,gòu,kěn,zhuó,zhuó zhào,shāng,dí,hèng,lán lín,a ā á ǎ à,cǎi,qiāng,zhūn tūn xiāng duǐ,wǔ,wèn,cuì qi,shà jié dié tì,gǔ,qǐ,qǐ,táo,dàn,dàn,yuē wā,zǐ cǐ,bǐ tú,cuì,chuò chuài,hé,yǎ yā,qǐ,zhé,fēi,liǎng,xián,pí,shá,lā la,zé,qíng yīng,guà,pā,zé shì,sè,zhuàn,niè,guō,luō luó luo,yán,dī,quán,tān chǎn tuō,bo,dìng,lāng,xiào,none,táng,chì,tí,ān án,jiū,dàn,kā,yóng,wèi,nán,shàn,yù,zhé,lǎ,jiē,hóu,hǎn,dié zhá,zhōu,chái,wāi,nuò rě,huò guó xù,yīn,zá zǎ,yāo,ō wō,miǎn,hú,yǔn,chuǎn,huì,huàn,huàn yuán xuǎn hé,xǐ,hē hè yè,jī,kuì,zhǒng chuáng,wéi wèi,shà,xǔ,huáng,duó zhà,yán,xuān,liàng,yù,sāng sàng,chī,qiáo jiāo,yàn,dān shàn chán,pèn bēn,cān sūn qī,lí,yō yo,zhā chā,wēi,miāo,yíng,pēn pèn,bǔ,kuí,xí,yù,jiē,lóu lou,kù,zào qiāo,hù,tí,yáo,hè xiāo xiào hù,shà á,xiù,qiāng qiàng,sè,yōng,sù,gòng hǒng gǒng,xié,yì ài,suō,má mǎ ma,chā,hài,kē kè,tà dā,sǎng,chēn,rù,sōu,wā gǔ,jī,bēng pǎng,wū,xián qiàn qiè,shì,gé,zī,jiē,lào,wēng,wà,sì,chī,háo,suō,jiā lún,hāi hēi,suǒ,qín,niè,hē,zi,sǎi,ň,gě,ná,diǎ,ǎi ài āi,qiāng,tōng,bì,áo,áo,lián,zuī suī,zhē zhè zhù zhe,mò,sòu,sǒu,tǎn,dí,qī,jiào,chōng,jiào dǎo,kǎi gě,tàn,shān càn,cáo,jiā,ái,xiào,piāo,lóu lou,gā gá gǎ,gǔ,xiāo jiāo,hū,huì,guō,ǒu,xiān,zé,cháng,xū shī,pó,dē dēi,ma má,mà,hú,lei lē,dū,gā gá gǎ,tāng,yě,bēng,yīng,sāi,jiào,mì,xiào,huá huā,mǎi,rán,zuō,pēng,lào láo,xiào,jī,zhǔ,cháo zhāo,kuì,zuǐ,xiāo,sī,háo,fǔ ,liáo,qiáo qiào,xī,chù xù shòu,tān chǎn,dàn tán,hēi mò,xùn,ě,zūn,fān bo,chī,huī,zǎn,chuáng,cù zā hé,dàn,jué,tūn kuò,cēng,jiào,yē,xī,qì,háo,lián,xū shī,dēng,huī,yín,pū,juē,qín,xún,niè,lū,sī,yǎn,yīng,dā,zhān,ō,zhòu zhuó,jìn,nóng,yuě huì,xiè,qì,è,zào,yī,shì,jiào qiào chī,yuàn,ǎi ài āi,yōng yǒng,jué xué,kuài,yǔ,pēn pèn,dào,gá,xīn hěn hèn,dūn,dāng,xīn,sāi,pī,pǐ,yīn,zuǐ,níng,dí,làn,tà,huò ǒ,rú,hāo,hè xià,yàn,duō,xiù pì,zhōu chóu,jì jiē zhāi,jìn,háo,tì,cháng,xūn,mē,cā chā,tì,lū,huì,bó pào bào,yōu,niè,yín,hù,mèi me mò,hōng,zhé,lí,liú,xié hái,náng,xiāo,mō,yàn,lì,lú,lóng,pó,dàn,chèn,pín,pǐ,xiàng,huò,mè,xī,duǒ,kù,yán,chán,yīng,rǎng rāng,diǎn,lá,tà,xiāo,jiáo jué jiào,chuò,huàn huān,huò,zhuàn,niè,xiāo,zá cà,lí,chǎn,chài,lì,yì,luō luó luo,náng nāng,zá zàn cān,sū,xǐ,zèng,jiān,yàn zá niè,zhǔ,lán,niè,nāng,lǎn,luó luō luo,wéi guó,huí,yīn,qiú,sì,nín,jiǎn nān,huí,xìn,yīn,nān,tuán,tuán,dùn tún,kàng,yuān,jiǒng,piān,yún,cōng,hú,huí,yuán,é,guó,kùn,cōng,wéi tōng,tú,wéi,lún,guó,qūn,rì,líng,gù,guó,tāi,guó,tú,yòu,guó,yín,hùn,pǔ,yǔ,hán,yuán,lún,quān juàn juān,yǔ,qīng,guó,chuán chuí,wéi,yuán,quān juàn juān,kū,pǔ,yuán,yuán,yà,tuān,tú,tú,tuán,lüè,huì,yì,huán yuán,luán,luán,tǔ,yà,tǔ,tǐng,shèng,pú,lù,kuài,yā,zài,wéi xū,gē,yù zhūn,wū,guī,pǐ,yí,dì de,qiān sú,qiān,zhèn,zhuó,dàng,qià,xià,shān,kuàng,cháng chǎng,qí yín,niè,mò,jī,jiá,zhǐ,zhǐ zhì,bǎn,xūn,yì,qǐn,méi fén,jūn,rǒng kēng,tún dùn,fāng fáng,bèn fèn,bèn,tān,kǎn,huài pēi pī péi,zuò,kēng,bì,jǐng,dì làn,jīng,jì,kuài,dǐ,jīng,jiān,tán,lì,bà,wù,fén,zhuì,pō,pǎn bàn,táng,kūn,qū,tǎn,zhǐ,tuó,gān,píng,diàn,guà,ní,tái,pī,jiōng,yǎng,fó,ào,lù,qiū,mù mǔ,kē kě,gòu,xuè,fá,dǐ chí,chè,líng,zhù,fù,hū,zhì,chuí,lā,lǒng,lǒng,lú,ào,dài,páo,mín,xíng,dòng tóng,jì,hè,lǜ,cí,chǐ,lěi,gāi,yīn,hòu,duī,zhào,fú,guāng,yáo,duǒ duò,duǒ duò,guǐ,chá,yáng,yín,fá,gòu,yuán,dié,xié,kěn,shǎng,shǒu,è,bìng,diàn,hóng,yà,kuǎ,dá,kǎ,dàng,kǎi,háng,nǎo,ǎn,xīng,xiàn,yuàn huán,bāng,póu fú,bà,yì,yìn,hàn,xù,chuí,cén,gěng,āi,běng fēng,dì fáng,què jué,yǒng,jùn,xiá jiā,dì,mái mán,làng,juǎn,chéng,yán shān,qín jīn,zhé,liè,liè,pǔ bù,chéng,huā,bù,shí,xūn,guō,jiōng,yě,niàn,dī,yù,bù,yà,quán,suì sù,pí pì,qīng zhēng,wǎn wān,jù,lǔn,zhēng chéng,kōng,chǒng shǎng,dōng,dài,tán tàn,ǎn,cǎi cài,chù tòu,běng,xiàn kǎn,zhí,duǒ,yì shì,zhí,yì,péi,jī,zhǔn,qí,sào sǎo,jù,ní,kū,kè,táng,kūn,nì,jiān,duī,jīn,gāng,yù,è,péng bèng,gù,tù,lèng líng,fāng,yá,qiàn zàn jiàn,kūn,àn,shēn,duò huī,nǎo,tū,chéng,yīn,huán,bì,liàn,guō,dié,zhuàn,hòu,bǎo bǔ pù,bǎo,yú,dī,máo móu wǔ,jiē,ruán,è ài yè,gèng,kān,zōng,yú,huáng,è,yáo,yàn,bào,jí,méi,cháng chǎng,dǔ,tuó,yìn,féng,zhòng,jiè,jīn,fēng,gāng,chuǎn,jiǎn,píng,lěi,jiǎng,huāng,léng,duàn,wān,xuān,jì,jí,kuài,yíng,tā,chéng,yǒng,kǎi,sù,sù,shí,mì,tǎ,wěng,chéng,tú,táng,què,zhǒng,lì,péng,bàng,sāi sài sè,zàng,duī,tián,wù,zhèng,xūn,gé,zhèn,ài,gōng,yán,xiàn,tián zhèn,yuán,wēn,xiè,liù,hǎi,lǎng,cháng chǎng,péng,bèng,chén,lù,lǔ,ōu qiū,qiàn zàn jiàn,méi,mò,zhuān tuán,shuǎng,shú,lǒu,chí,màn,biāo,jìng,qī,shù,zhì dì,zhàng,kàn,yōng,diàn,chěn,zhǐ zhuó,xì,guō,qiǎng,jìn,dì,shāng,mù,cuī,yàn,tǎ,zēng,qián,qiáng,liáng,wèi,zhuì,qiāo,zēng,xū,shàn,shàn,fá,pú,kuài tuí,tuǎn dǒng,fán,qiáo què,mò,dūn,dūn,zūn dūn,dì,shèng,duò huī,duò,tán,dèng,wú,fén,huáng,tán,dā,yè,zhù,jiàn,ào,qiáng,jī,qiāo áo,kěn,yì tú,pí,bì,diàn,jiāng,yě,yōng,xué bó jué,tán,lǎn,jù,huài,dàng,rǎng,qiàn,xūn,xiàn làn,xǐ,hè,ài,yā yà,dǎo,háo,ruán,jìn,lěi,kuàng,lú,yán,tán,wéi,huài,lǒng,lǒng,ruǐ,lì,lín,rǎng,chán,xūn,yán,lěi,bà,wān,shì,rén,san,zhuàng,zhuàng,shēng,yī,mài,ké qiào,zhù,zhuàng,hú,hú,kǔn,yī,hú,xù,kǔn,shòu,mǎng,cún,shòu,yī,zhǐ zhōng,gǔ yíng,chǔ chù,jiàng xiáng,féng fēng páng,bèi,zhāi,biàn,suī,qūn,líng,fù,cuò,xià,xiòng xuàn,xiè,náo,xià,kuí,xī,wài,yuàn wǎn wān yuān,mǎo wǎn,sù,duō,duō,yè,qíng,wài,gòu,gòu,qì,mèng,mèng,yín,huǒ,chěn,dà dài tài,cè,tiān,tài,fū fú,guài,yāo,yāng,hāng bèn,gǎo,shī,tāo běn,tài,tóu tou,yǎn tāo,bǐ,yí,kuā kuà,jiā jiá gā xiá,duó,huà,kuǎng,yǔn,jiā jiá gā xiá,bā,ēn,lián,huàn,dī tì,yǎn yān,pào,juàn,qí jī,nài,fèng,xié,fèn,diǎn,quān juàn,kuí,zòu,huàn,qì qiè 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liáo,bèn,fǔ,qiào,bō,cuō zuǒ,zhuó,zhuàn,wěi tuǒ,pū,qìn,dūn,niǎn,huá,xié,lū,jiǎo,cuān,tà,hàn,qiào yāo jī,zhuā wō,jiǎn,gǎn,yōng,léi lèi,nǎng,lǔ,shàn,zhuó,zé zhái,pǔ,chuò,jī,dǎng dàng,sè,cāo,qíng,qíng jǐng,huàn,jiē,qín,kuǎi,dān dàn,xié,qiā jiā yè,pǐ bò,bò bāi,ào,jù jū,yè,è,mēng,sòu sǒu,mí,jǐ,tái,zhuó,dǎo,xǐng,lǎn,cā,jǔ,yē,rǔ,yè,yè,nǐ,huò,jié,bìn,níng nǐng nìng,gē gé,zhì,zhì jié,kuò,mó,jiàn,xié,liè là,tān,bǎi,sòu sǒu,lū,lì luò yuè,rǎo,tī zhì zhāi,pān,yǎng,léi lèi,cā sǎ,shū,zǎn,niǎn,xiǎn,jùn pèi,huō,lì luò,là lài,huàn,yíng,lú luó,lǒng,qiān,qiān,zǎn cuán,qiān,lán,xiān jiān,yīng,méi,rǎng,chān,wěng,cuān,xié,shè niè,luó,jùn,mí mǐ mó,chī,zǎn cuán,luán,tān,zuàn,lì shài,diān,wā,dǎng,jiǎo,jué,lǎn,lì luǒ,nǎng,zhī,guì,guǐ guì,qī yǐ jī,xún,pū,pū,shōu,kǎo,yōu,gǎi,yǐ,gōng,gān hàn,bān,fàng,zhèng,pò,diān,kòu,mǐn,wù móu,gù,hé,cè,xiào,mǐ,chù shōu,gé guó è,dí,xù,jiào jiāo,mǐn,chén,jiù,shēn,duó duì,yǔ,chì,áo,bài,xù,jiào jiāo,duó duì,liǎn,niè,bì,chǎng,diǎn,duō què,yì,gǎn,sàn sǎn,kě,yàn,dūn duì,qī yǐ jī,tǒu,xiào xué,duō què,jiǎo,jìng,yáng,xiá,mǐn,shù shǔ shuò,ái zhú,qiāo,ái zhú,zhěng,dí,chén,fū,shù shǔ shuò,liáo,qū,xiòng xuàn,yǐ,jiǎo,shàn,jiǎo,zhuó zhú,yì dù,liǎn,bì,lí tái,xiào,xiào,wén,xué,qí,qí,zhāi,bīn,jué jiào,zhāi,láng,fěi fēi,bān,bān,lán,yǔ zhōng,lán,wěi mén,dǒu dòu,shēng,liào,jiǎ,hú,xié,jiǎ,yǔ,zhēn,jiào,wò guǎn,tǒu tiǎo,dòu,jīn,chì,yín zhì,fǔ,qiāng,zhǎn,qú,zhuó,zhǎn,duàn,zhuó,sī,xīn,zhuó,zhuó,qín,lín,zhuó,chù,duàn,zhú,fāng,chǎn jiè,háng,yú wū,shī,pèi,liú yóu,mèi,páng bàng,qí,zhān,máo mào,lǚ,pèi,pī bì,liú,fū,fǎng,xuán xuàn,jīng,jīng,nǐ,zú,zhào,yǐ,liú,shāo,jiàn,yú,yǐ,qí,zhì,fān,piāo,fān,zhān,kuài,suì,yú,wú,jì,jì,jì,huò,rì,dàn,jiù,zhǐ,zǎo,xié,tiāo,xún,xù,gā,lá,gàn hàn,hàn,tái yīng,dì dí de,xù xū,chǎn,shí,kuàng,yáng,shí,wàng,mín,mín,tūn zhùn,chūn,wù wǔ,yún,bèi,áng,zè,bǎn,jié,kūn,shēng,hù,fǎng,hào,guì,chāng,xuān,míng,hūn,fēn,qǐn,hū,yì,xī,xīn,yán,zè,fǎng,tán,shèn,jù,yáng,zǎn,bǐng,xīng,yìng,xuàn,pò,zhěn,líng,chūn,hào,mèi,zuó,mò,biàn,xù,hūn,zhāo,zòng,shì,shì,yù,fèi,dié yì,mǎo,nì,chǎng,wēn,dōng,ǎi,bǐng,áng,zhòu,lóng,xiǎn,kuàng,tiǎo,cháo,shí,huǎng huàng,huǎng,xuān,kuí,xù kuā,jiǎo,jìn,zhì,jìn,shǎng,tóng,hǒng,yàn,gāi,xiǎng,shài,xiǎo,yè,yùn yūn,huī,hán,hàn,jùn,wǎn,xiàn,kūn,zhòu,xī,shèng chéng,shèng,bū,zhé,zhé,wù,wǎn,huì,hào,chén,wǎn,tiǎn,zhuó,zuì,zhǒu,pǔ,jǐng yǐng,xī,shǎn,nǐ,xī,qíng,qǐ dù,jīng,guǐ,zhěng,yì,zhì,àn ǎn yǎn,wǎn,lín,liàng,chēng,wǎng wàng,xiǎo,zàn,fēi,xuān,xuǎn,yí,xiá,yùn yūn,huī,xǔ,mǐn mín,kuí,yē,yìng,shǔ dǔ,wěi,shǔ,qíng,mào,nán,jiǎn lán,nuǎn,àn,yáng,chūn,yáo,suǒ,pǔ,míng,jiǎo,kǎi,hào,wěng,chàng,qì,hào,yàn,lì,ài,jì,jì,mèn,zàn,xiè,hào,mù,mù,cōng,nì,zhāng,huì,bào pù,hàn,xuán,chuán,liáo,xiān,tǎn,jǐng,piē,lín,tūn,xī xǐ,yì,jì,huàng,dài,yè,yè,lì,tán,tóng,xiǎo,fèi,shěn,zhào,hào,yì,xiàng,xīng,shēn,jiǎo,bào,jìng,yàn,ài,yè,rú,shǔ,méng,xūn,yào,pù bào,lì,chén,kuàng,dié,liǎo,yàn,huò,lú,xī,róng,lóng,nǎng,luǒ,luán,shài,tǎng,yǎn,zhú,yuē,yuē,qū qǔ,yè,gēng gèng,yè,hū hù,hé,shū,cáo,cáo,shēng,màn,zēng céng,zēng céng,tì,zuì,cǎn qián jiàn,xù,huì kuài,yǐn,qiè hé,fēn,bì pí,yuè,yǒu yòu,ruǎn,péng,fén bān,fú fù,líng,fěi kū,qú xù chǔn,tì,nǜ gǎ,tiǎo,shuò,zhèn,lǎng,lǎng,juān zuī,míng,huāng máng wáng,wàng,tūn,zhāo cháo,jī,qī jī,yīng,zōng,wàng,tóng chuáng,lǎng,láo,méng,lóng,mù,pìn děng,wèi,mò,běn,zhá,shù shú zhú,shù shú zhú,none,zhū shú,rén,bā,pǔ pò pō piáo,duǒ,duǒ,dāo tiáo mù,lì,qiú guǐ,jī,jiū,bǐ,xiǔ,chéng chēng,cì,shā,rù,zá,quán,qiān,yú wū,gān gǎn,wū,chā chà,shā,xún,fán,wù,zǐ,lǐ,xìng,cái,cūn,rèn ér,sháo biāo,tuō zhé,dì duò,zhàng,máng,chì,yì,gū gài,gōng,dù,yí lì lí duò tuò,qǐ,shù,gàng gāng,tiáo tiāo,jié,mián,wàn,lái,jiǔ,máng,yáng,mà mǎ,miǎo,sì zhǐ xǐ,yuán wán,háng,fèi bèi,bēi,jié,dōng,gǎo,yǎo,xiān,chǔ,chūn,pá,shū duì,huà,xīn,niǔ chǒu,zhù,chǒu,sōng,bǎn,sōng,jí,wò yuè,jìn,gòu,jī,máo,pí,pī mì,wǎng,àng,fāng bìng,fén,yì,fú fū,nán,xī,hù dǐ,yā,dōu,xín,zhěn,yǎo yāo,lín,ruì,ě è,méi,zhào,guǒ,zhī qí,cōng zōng,yùn,huà,shēng,shū,zǎo,dì duò,lì,lú,jiǎn,chéng,sōng,qiāng,fēng,zhān,xiāo,xiān zhēn,kū,píng,sì tái,xǐ,zhǐ,guǎi,xiāo,jià,jiā,jǔ gǒu,bāo fú,mò,yì 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biě,jì,chī,yǎng,xuǎn,jiē,zhēng,mèng,lì,huò,lài,jī,diān,xuǎn,yǐng,yǐn,qú,yōng,tān,diān,luǒ,luán,luán,bō,bō bǒ,guǐ,bá,fā,dēng,fā,bái,bǎi,qié,jí bī,zào,zào,mào,de dí dì,pā bà,jiē,huáng,guī,cǐ,líng,gāo háo,mò,jí,jiǎo,pěng,gāo yáo,ái,é,hào,hàn,bì,wǎn,chóu,qiàn,xī,ái,xiǎo,hào,huàng,hào,zé,cuǐ,hào,xiǎo,yè,pó,hào,jiǎo,ài,xīng,huàng,lì luò bō,piǎo,hé,jiào,pí,gǎn,pào,zhòu,jūn,qiú,cūn,què,zhā,gǔ,jūn,jūn,zhòu,zhā cǔ,gǔ,zhāo zhǎn dǎn,dú,mǐn,qǐ,yíng,yú,bēi,diào,zhōng,pén,hé,yíng,hé,yì,bō,wǎn,hé,àng,zhǎn,yán,jiān jiàn,hé,yū,kuī,fàn,gài gě hé,dào,pán,fǔ,qiú,shèng chéng,dào,lù,zhǎn,méng,lí,jìn,xù,jiān jiàn,pán,guàn,ān,lú,xǔ,zhōu chóu,dàng,ān,gǔ,lì,mù,dīng,gàn,xū,máng,máng wàng,zhí,qì,yuǎn,xián tián,xiāng xiàng,dǔn,xīn,xì pǎn,pàn,fēng,dùn,mín,míng,shěng xǐng,shì,yún hùn,miǎn,pān,fǎng,miǎo,dān,méi,mào,kàn kān,xiàn,kōu,shì,yāng yǎng yìng,zhēng,yǎo āo ǎo,shēn,huò,dà,zhěn,kuàng,jū xū kōu,shèn,yí chì,shěng,mèi,mò miè,zhù,zhēn,zhēn,mián,shì,yuān,dié tì,nì,zì,zì,chǎo,zhǎ,xuàn,bǐng fǎng,pàng pán,lóng,guì 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lèi,jìn,shèn,gāi,kǔn,dì,dǎo,huò,táo,qí,gù,guàn,zuì,líng,lù,bǐng,jīn jìn,dǎo,zhí,lù,chán shàn,bì pí,chǔ,huī,yǒu,xì,yīn,zī,huò,zhēn,fú,yuàn,xú,xiǎn,shāng yáng,tí zhǐ,yī,méi,sī,dì,bèi,zhuó,zhēn,yíng,jì,gào,táng,sī,mà,tà,fù,xuān,qí,yù,xǐ,jī jì,sì,shàn chán,dàn,guì,suì,lǐ,nóng,mí,dǎo,lì,ráng,yuè,tí,zàn,lèi,róu,yǔ,yú yù ǒu,lí,xiè,qín,hé,tū,xiù,sī,rén,tū,zǐ zì,chá ná,gǎn,yì zhí,xiān,bǐng,nián,qiū,qiū,zhǒng zhòng chóng,fèn,hào mào,yún,kē,miǎo,zhī,jīng,bǐ,zhǐ,yù,mì bì,kù kū,bàn,pī,ní nì,lì,yóu,zū,pī,bó,líng,mò,chèng,nián,qín,yāng,zuó,zhì,dī,shú,jù,zǐ,huó kuò,jī,chēng chèn chèng,tóng,shì zhì,huó kuò,huō,yīn,zī,zhì,jiē,rěn,dù,yí,zhū,huì,nóng,fù pū,xī,gǎo,láng,fū,xùn zè,shuì,lǚ,kǔn,gǎn,jīng,tí,chéng,tú shǔ,shāo shào,shuì,yà,lǔn,lù,gū,zuó,rěn,zhùn zhǔn,bàng,bài,jī qí,zhī,zhì,kǔn,léng lēng líng,péng,kē,bǐng,chóu,zuì zú sū,yù,sū,lüè,xiāng,yī,xì qiè,biǎn,jì,fú,pì bì,nuò,jiē,zhǒng zhòng,zōng zǒng,xǔ xū,chēng chèn chèng,dào,wěn,xián jiān liàn,zī jiū,yù,jì,xù,zhěn,zhì,dào,jià,jī 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fěng,yáng,zhǎn,biāo,sà,jù,sī,sōu,yáo,liú,piāo,biāo,biāo,fēi,fān,fēi,fēi,shí sì yì,shí,cān,jī,dìng,sì,tuō,zhān,sūn,xiǎng,tún,rèn,yù,yǎng juàn,chì,yǐn yìn,fàn,fàn,sūn,yǐn yìn,zhù tǒu,yí sì,zuò zé zhā,bì,jiě,tāo,bǎo,cí,tiè,sì,bǎo,shì,duò,hài,rèn,tiǎn,jiǎo,hé,bǐng,yáo,tóng,cí,xiǎng,yǎng,juàn,ěr,yàn,lè,xī,cān,bō,něi,è,bū,jùn,dòu,sù,yú,shì,yáo,hún,guǒ,shì,jiàn,chuò,bǐng,xiàn,bù,yè,dàn,fēi,zhāng,wèi,guǎn,è,nuǎn,yùn,hú,huáng,tiè,huì,jiān,hóu,ài,xíng,fēn,wèi,gǔ,chā,sòng,táng,bó,gāo,xì,kuì,liù,sōu,táo,yè,wēn,mó,táng,mán,bì,yù,xiū,jǐn,sǎn,kuì,zhuàn,shàn,xī,dàn,yì,jī,ráo,chēng,yōng,tāo,wèi,xiǎng,zhān,fēn,hài,méng,yàn,mó,chán,xiǎng náng,luó,zàn,náng,shí,dìng,jī,tuō,xíng,tún,xì,rèn,yù,chì,fàn,yǐn,jiàn,shì,bǎo,sì,duò,yí,ěr,ráo,xiǎng,hé,gē le,jiǎo,xī,bǐng,bō,dòu,è,yú,něi,jùn,guǒ,hún,xiàn,guǎn,chā,kuì,gǔ,sōu,chán,yè,mó,bó,liù liú,xiū,jǐn,mán,sǎn,zhuàn,náng nǎng,shǒu,kuí,guó,xiāng,fēn,bó,ní,bì,bó,tú,hān,fēi,jiān,ān,ài,fù,xiān,yūn wò,xīn,fén,pīn,xīn,mǎ,yù,féng píng,hàn hán,dí,tuó duò,tuō zhé,chí,xùn,zhù,zhī shì,pèi,xìn jìn,rì,sà,yǔn,wén,zhí,dǎn dàn,lú,yóu,bó,bǎo,jué kuài,tuó duò,yì,qū,wén,qū,jiōng,pǒ,zhāo,yuān,pēng,zhòu,jù,zhù,nú,jū,pī,zǎng,jià,líng,zhěn,tái dài,fù,yǎng,shǐ,bì,tuó,tuó,sì,liú,mà,pián,táo,zhì,róng,téng,dòng,xún xuān,quán,shēn,jiōng,ěr,hài,bó,zhū,yīn,luò,zhōu,dàn,hài,liú,jú,sǒng,qīn,máng,liáng láng,hàn,tú,xuān,tuì,jùn,ě,chěng,xīng,sì,lù,zhuī,zhōu,shè,pián,kūn,táo,lái,zōng,kè,qí,qí,yàn,fēi,sāo,yàn,gé,yǎo,wù,piàn,cōng,piàn,qián,fēi,huáng,qián,huō,yú,tí,quán,xiá,zōng,kuí,róu,sī,guā,tuó,guī,sōu,qiān,chéng,zhì,liú,péng,téng,xí,cǎo,dú,yàn,yuán,zōu,sāo,shàn,qí,zhì,shuāng,lù,xí,luó,zhāng,mò,ào,cān,piào,cōng,qū,bì,zhì,yù,xū,huá,bō,sù,xiāo,lín,zhàn,dūn,liú,tuó,céng,diàn,jiāo,tiě,yàn,luó,zhān,jīng,yì,yè,tuó,pīn,zhòu,yàn,lóng,lǘ,téng,xiāng,jì,shuāng,jú,xí,huān,lí,biāo,mǎ,yù,tuó,xùn,chí,qū,rì,bó,lǘ,zǎng,shǐ,sì,fù,jū,zōu,zhù,tuó,nú,jià,yì,tái,xiāo,mà,yīn,jiāo,huá,luò,hài,pián,biāo,lí,chěng,yàn,xīng,qīn,jùn,qí,qí,kè,zhuī,zōng,sù,cān,piàn,zhì,kuí,sāo sǎo,wù,áo,liú,qiān,shàn,piào biāo,luó,cōng,chǎn,zhòu,jì,shuāng,xiāng,gǔ gū,wěi,wěi,wěi,yú,gàn,yì,āng,tóu,jiè,bào,bèi mó,cī,tǐ,dǐ,kū,hái,qiāo xiāo,hóu,kuà,gé,tuǐ,gěng,pián,bì,kē,qià,yú,suí,lóu,bó,xiāo,bǎng,bó jué,cī,kuān,bìn,mó,liáo,lóu,xiāo,dú,zāng,suǐ,tǐ tī,bìn,kuān,lú,gāo,gāo,qiào,kāo,qiǎo,láo,sào,biāo,kūn,kūn,dí,fǎng,xiū,rán,máo,dàn,kūn,bìn,fà,tiáo,pī,zī,fà,rán,tì,bào,bì pǒ,máo méng,fú,ér,èr,qū,gōng,xiū,kuò yuè,jì,péng,zhuā,shāo,shā,tì,lì,bìn,zōng,tì,péng,sōng,zhēng,quán,zōng,shùn,jiǎn,duǒ,hú,là,jiū,qí,lián,zhěn,bìn,péng,mà,sān,mán,mán,sēng,xū,liè,qiān,qiān,nóng,huán,kuò,níng,bìn,liè,ráng,dòu,dòu,nào,hòng,xì,dòu,kàn,dòu,dòu,jiū,chàng,yù,yù,gé lì,yàn,fǔ,zèng,guī,zōng,liù,guī,shāng,yù,guǐ,mèi,jì,qí,gà,kuí,hún,bá,pò,mèi,xū,yǎn,xiāo,liǎng,yù,tuí,qī,wǎng,liǎng,wèi,gān,chī,piāo,bì,mó,jī,xū,chǒu,yǎn,zhān,yú,dāo,rén,jì,bā bà,hóng,tuō,diào,jǐ,yú,é,jì,shā,háng,tún,mò,jiè,shěn,bǎn,yuán,pí,lǔ,wén,hú,lú,zā,fáng,fén,nà,yóu,piàn,mó,hé,xiá,qū,hān,pī,líng,tuó,bà,qiú,píng,fú,bì,cǐ jì,wèi,jū,diāo,bó bà,yóu,gǔn,pí,nián,xīng,tái,bào,fù,zhǎ zhà,jù,gū,shí,dōng,chou dài,tǎ,jié,shū,hòu,xiǎng,ér,ān,wéi,zhào,zhū,yìn,liè,luò gé,tóng,yí,yì,bìng,wěi,jiāo,kū,guī xié wā kuí,xiān xiǎn,gé,huí,lǎo,fú,kào,xiū,tuō,jūn,tí,miǎn,shāo,zhǎ,suō,qīn,yú,něi,zhé,gǔn,gěng,sū,wú,qiú,shān,pū bū,huàn,tiáo,lǐ,shā,shā,kào,méng,chéng,lí,zǒu,xī,yǒng,shēn,zī,qí,qīng,xiǎng,něi,chún,jì,diāo,qiè,gù,zhǒu,dōng,lái,fēi,ní,yì sī,kūn,lù,jiù,chāng,jīng,lún,líng,zōu,lí,měng,zōng,zhì,nián,hǔ,yú,dǐ,shī,shēn,huàn,tí,hóu,xīng,zhū,là,zōng,jì,biān,biān,huàn,quán,zéi,wēi,wēi,yú,chūn,róu,dié,huáng,liàn,yǎn,qiū,qiū,jiǎn,bī,è,yáng,fù,sāi,jiān,xiā,tuǒ,hú,shì,ruò,xuān,wēn,jiān,hào,wū,páng,sāo,liú,mǎ,shí,shī,guān,zī,téng,tǎ,yáo,è,yóng,qián,qí,wēn,ruò,shén,lián,áo,lè,huī,mǐn,jì,tiáo,qū,jiān,shēn,mán,xí,qiú,piào,jì,jì,zhú,jiāng,xiū,zhuān,yōng,zhāng,kāng,xuě,biē,yù,qū,xiàng,bō,jiǎo,xún,sù,huáng,zūn,shàn,shàn,fān,guì,lín,xún,yáo,xǐ,zēng,xiāng,fèn,guān,hòu,kuài,zéi,sāo,zhān,gǎn,guì,yìng,lǐ,cháng,léi,shǔ,ài,rú,jì,xù,hù,shǔ,lǐ,liè,lè,miè,zhēn,xiǎng,è,lú,guàn,lí,xiān,yú,dāo,jǐ,yóu,tún,lǔ,fáng,bā bà,hé gě,bà,píng,nián,lú,yóu,zhǎ zhà,fù,bó bà,bào,hòu,pí,tái,guī xié,jié,kào,wěi,ér,tóng,zéi,hòu,kuài,jì,jiāo,xiān xiǎn,zhǎ,xiǎng,xún,gěng,lí,lián,jiān,lǐ,shí,tiáo,gǔn,shā,huàn,jūn,jì,yǒng,qīng,líng,qí,zōu,fēi,kūn,chāng,gù,ní,nián,diāo,jīng,shēn,shī,zī,fèn,dié,bī,cháng,tí,wēn,wēi,sāi xǐ,è,qiū,fù,huáng,quán,jiāng,biān,sāo,áo,qí,tǎ,guān,yáo,páng,jiān,lè,biào,xuě,biē,mán,mǐn,yōng,wèi,xí,guì jué,shàn,lín,zūn,hù,gǎn,lǐ,zhān shàn,guǎn,niǎo diǎo,yǐ,fú,lì,jiū,bú,yàn,fú,diāo zhāo,jī,fèng,rù,gān hàn yàn,shī,fèng,míng,bǎo,yuān,zhī,hù,qín,fū guī,bān fén,wén,jiān qiān zhān,shī,yù,fǒu,yāo,jué,jué,pǐ,huān,zhèn,bǎo,yàn,yā,zhèng,fāng,fèng,wén,ōu,dài,jiā,rú,líng,miè,fú,tuó,mín,lì,biǎn,zhì,gē,yuān,cí,qú,xiāo,chī,dàn,jū,yāo,gū,zhōng,yù,yāng,yù,yā,dié,yù,tián,yīng,duī,wū,ér,guā,ài,zhī,yàn,héng,xiāo,jiá,liè,zhū,yáng,yí,hóng,lù,rú,móu,gē,rén,jiāo,xiū,zhōu,chī,luò,héng,nián,ě,luán,jiá,jì,tú,huān,tuǒ,bū,wú,jiān,yù,bó,jùn,jùn,bī,xī,jùn,jú,tū,jìng,tí,é,é,kuáng,hú,wǔ,shēn,lài,zān,pàn,lù,pí,shū,fú,ān,zhuó,péng,qín,qiān,bēi,diāo,lù,què,jiān,jú,tù,yā,yuān,qí,lí,yè,zhuī,kōng,duò,kūn,shēng,qí,jīng,yì,yì,jīng,zī,lái,dōng,qī,chún,gēng,jū,qū,yì,zūn,jī,shù,yīng,chì,miáo,róu,ān,qiū,tí chí,hú,tí chí,è,jiē,máo,fú bì,chūn,tú,yǎn,hé jiè,yuán,piān biǎn,kūn,méi,hú,yīng,chuàn zhì,wù,jú,dōng,cāng qiāng,fǎng,hè hú,yīng,yuán,xiān,wēng,shī,hè,chú,táng,xiá,ruò,liú,jī,gǔ hú,jiān,sǔn xùn,hàn,cí,cí,yì,yào,yàn,jī,lì,tián,kòu,tī,tī,yì,tú,mǎ,xiāo,gāo,tián,chén,jì,tuán,zhè,áo,yǎo,yī,ōu,chì,zhì,liù,yōng,lóu lǚ,bì,shuāng,zhuó,yú,wú,jué,yín,tí,sī,jiāo,yì,huá,bì,yīng,sù,huáng,fán,jiāo,liáo,yàn,gāo,jiù,xián,xián,tú,mǎi,zūn,yù,yīng,lù,tuán,xián,xué,yì,pì,zhǔ,luó,xī,yì,jī,zé,yú,zhān,yè,yáng,pì,níng,hù,mí,yīng,méng,dí,yuè,yù,lěi,bǔ,lú,hè,lóng,shuāng,yuè,yīng,guàn,qú,lí,luán,niǎo,jiū,jī,yuān,míng,shī,ōu,yā,cāng,bǎo,zhèn,gū,dōng,lú,yā,xiāo,yāng,líng,chī,qú,yuān,xué,tuó,sī,zhì,ér,guā,xiū,héng,zhōu,gē,luán,hóng,wú,bó,lí,juān,hú,é,yù,xián,tí,wǔ,què,miáo,ān,kūn,bēi,péng,qiān,chún,gēng,yuān,sù,hú,hé,è,gǔ,qiū,cí,méi,wù,yì,yào,wēng,liú,jī,yì,jiān,hè,yī,yīng,zhè,liù,liáo,jiāo,jiù,yù,lù,huán,zhān,yīng,hù,méng,guàn,shuāng,lǔ,jīn,líng,jiǎn,xián,cuó,jiǎn,jiǎn,yán,cuó,lù,yōu,cū,jǐ,páo biāo,cū,páo,zhù cū,jūn qún,zhǔ,jiān,mí,mí,yǔ,liú,chén,jūn,lín,ní,qí,lù,jiù,jūn,jīng,lí lì,xiāng,xián,jiā,mí,lì,shè,zhāng,lín,jīng,qí,líng,yán,cū,mài,mài,hé,chǎo,fū,miàn,miàn,fū,pào,qù,qū,móu,fū,xiàn,lái,qū,miàn,chi,fēng,fū,qū,miàn,má,mó me,mó me,huī,mí,zōu,nún,fén,huáng,huáng,jīn,guāng,tiān,tǒu,hóng,huà,kuàng,hóng,shǔ,lí,nián,chī,hēi,hēi,yì,qián,dǎn,xì,tún,mò,mò,qián,dài,chù,yǒu,diǎn,yī,xiá,yǎn,qū,měi,yǎn,qíng,yuè,lí,dǎng,dú,cǎn,yān,yǎn,yǎn,dàn shèn,àn,zhěn yān,dài,cǎn,yī,méi,dǎn zhǎn,yǎn,dú,lú,zhǐ,fěn,fú,fǔ,mǐn miǎn měng,mǐn miǎn měng,yuán,cù,qù,cháo,wā,zhū,zhī,měng,áo,biē,tuó,bì,yuán,cháo,tuó,dǐng,mì,nài,dǐng,zī,gǔ,gǔ,dōng,fén,táo,yuān,pí,chāng,gāo,cào,yuān,tāng,tēng,shǔ,shǔ,fén,fèi,wén,bá,diāo,tuó,zhōng,qú,shēng,shí,yòu,shí,tíng,wú,jú,jīng,hún,jú,yǎn,tū,sī,xī,xiàn,yǎn,léi,bí,yào,qiú,hān,wù,wù,hōu,xiè,è,zhā,xiù,wèng,zhā,nòng,nàng,qí zhāi,zhāi,jì,zī,jí,jī,qí jì zī zhāi,jī,chǐ,chèn,chèn,hé,yá,yīn,xiè,bāo,zé,xiè,zī,chī,yàn,jǔ,tiáo,líng,líng,chū,quán,xiè,yín,niè,jiù,yǎo,chuò,yǔn,yǔ,chǔ,yǐ,ní,zé,zōu,qǔ,yǔn,yǎn,yú,è,wò,yì,cī,zōu,diān,chǔ,jìn,yà,chǐ,chèn,hé,yín kěn,jǔ,líng,bāo,tiáo,zī,yín kěn,yǔ,chuò,qǔ,wò,lóng lǒng,páng,gōng wò,páng,yǎn,lóng,lóng lǒng,gōng,kān,dá,líng,dá,lóng,gōng,kān,guī jūn qiū,qiū,biē,guī jūn qiū,yuè,chuī,hé,jiǎo,xié,yù";

    pinyinUtil.js 

    /**
     * 汉字与拼音互转工具,根据导入的字典文件的不同支持不同
     * 对于多音字目前只是将所有可能的组合输出,准确识别多音字需要完善的词库,而词库文件往往比字库还要大,所以不太适合web环境。
     */
    ;(function()
    {
    	var dict = {}; // 存储所有字典数据
    	var pinyinUtil =
    	{
    		/**
    		 * 解析各种字典文件,所需的字典文件必须在本JS之前导入
    		 */
    		parseDict: function()
    		{
    			// 如果导入了 pinyin_dict_firstletter.js
    			if(window.pinyin_dict_firstletter)
    			{
    				dict.firstletter = pinyin_dict_firstletter;
    			}
    			// 如果导入了 pinyin_dict_notone.js
    			if(window.pinyin_dict_notone)
    			{
    				dict.notone = {};
    				dict.py2hz = pinyin_dict_notone; // 拼音转汉字
    				for(var i in pinyin_dict_notone)
    				{
    					var temp = pinyin_dict_notone[i];
    					for(var j=0, len=temp.length; j<len; j++)
    					{
    						dict.notone[temp[j]] = i; // 不考虑多音字
    					}
    				}
    			}
    			// 如果导入了 pinyin_dict_withtone.js
    			if(window.pinyin_dict_withtone)
    			{
    				dict.withtone = {};
    				var temp = pinyin_dict_withtone.split(',');
    				for(var i=0, len = temp.length; i<len; i++)
    				{
    					// 这段代码耗时28毫秒左右,对性能影响不大,所以一次性处理完毕
    					dict.withtone[String.fromCharCode(i + 19968)] = temp[i]; // 这里先不进行split(' '),因为一次性循环2万次split比较消耗性能
    				}
    
    				// 拼音 -> 汉字
    				if(window.pinyin_dict_notone)
    				{
    					// 对于拼音转汉字,我们优先使用pinyin_dict_notone字典文件
    					// 因为这个字典文件不包含生僻字,且已按照汉字使用频率排序
    					dict.py2hz = pinyin_dict_notone; // 拼音转汉字
    				}
    				else
    				{
    					// 将字典文件解析成拼音->汉字的结构
    					// 与先分割后逐个去掉声调相比,先一次性全部去掉声调然后再分割速度至少快了3倍,前者大约需要120毫秒,后者大约只需要30毫秒(Chrome下)
    					var notone = pinyinUtil.removeTone(pinyin_dict_withtone).split(',');
    					var py2hz = {}, py, hz;
    					for(var i=0, len = notone.length; i<len; i++)
    					{
    						hz = String.fromCharCode(i + 19968); // 汉字
    						// = aaa[i];
    						py = notone[i].split(' '); // 去掉了声调的拼音数组
    						for(var j=0; j<py.length; j++)
    						{
    							py2hz[py[j]] = (py2hz[py[j]] || '') + hz;
    						}
    					}
    					dict.py2hz = py2hz;
    				}
    			}
    		},
    		/**
    		 * 根据汉字获取拼音,如果不是汉字直接返回原字符
    		 * @param chinese 要转换的汉字
    		 * @param splitter 分隔字符,默认用空格分隔
    		 * @param withtone 返回结果是否包含声调,默认是
    		 * @param polyphone 是否支持多音字,默认否
    		 */
    		getPinyin: function(chinese, splitter, withtone, polyphone)
    		{
    			if(!chinese || /^ +$/g.test(chinese)) return '';
    			splitter = splitter == undefined ? ' ' : splitter;
    			withtone = withtone == undefined ? true : withtone;
    			polyphone = polyphone == undefined ? false : polyphone;
    			var result = [];
    			if(dict.withtone) // 优先使用带声调的字典文件
    			{
    				for (var i=0, len = chinese.length; i < len; i++)
    				{
    					var pinyin = dict.withtone[chinese[i]];
    					if(pinyin)
    					{
    						if(!polyphone) pinyin = pinyin.replace(/ .*$/g, ''); // 如果不需要多音字
    						if(!withtone) pinyin = this.removeTone(pinyin); // 如果不需要声调
    					}
    					result.push(pinyin || chinese[i]); 
    				}
    			}
    			else if(dict.notone) // 使用没有声调的字典文件
    			{
    				if(withtone) console.warn('pinyin_dict_notone 字典文件不支持声调!');
    				if(polyphone) console.warn('pinyin_dict_notone 字典文件不支持多音字!');
    				for (var i=0, len = chinese.length; i < len; i++)
    				{
    					var temp = chinese.charAt(i);
    					result.push(dict.notone[temp] || temp); 
    				}
    			}
    			else
    			{
    				throw '抱歉,未找到合适的拼音字典文件!';
    			}
    			if(!polyphone) return result.join(splitter);
    			else
    			{
    				if(window.pinyin_dict_polyphone) return parsePolyphone(chinese, result, splitter, withtone);
    				else return handlePolyphone(result, ' ', splitter);
    			}
    		},
    		/**
    		 * 获取汉字的拼音首字母
    		 * @param str 汉字字符串,如果遇到非汉字则原样返回
    		 * @param polyphone 是否支持多音字,默认false,如果为true,会返回所有可能的组合数组
    		 */
    		getFirstLetter: function(str, polyphone)
    		{
    			polyphone = polyphone == undefined ? false : polyphone;
    			if(!str || /^ +$/g.test(str)) return '';
    			if(dict.firstletter) // 使用首字母字典文件
    			{
    				var result = [];
    				for(var i=0; i<str.length; i++)
    				{
    					var unicode = str.charCodeAt(i);
    					var ch = str.charAt(i);
    					if(unicode >= 19968 && unicode <= 40869)
    					{
    						ch = dict.firstletter.all.charAt(unicode-19968);
    						if(polyphone) ch = dict.firstletter.polyphone[unicode] || ch;
    					}
    					result.push(ch);
    				}
    				if(!polyphone) return result.join(''); // 如果不用管多音字,直接将数组拼接成字符串
    				else return handlePolyphone(result, '', ''); // 处理多音字,此时的result类似于:['D', 'ZC', 'F']
    			}
    			else
    			{
    				var py = this.getPinyin(str, ' ', false, polyphone);
    				py = py instanceof Array ? py : [py];
    				var result = [];
    				for(var i=0; i<py.length; i++)
    				{
    					result.push(py[i].replace(/(^| )(\w)\w*/g, function(m,$1,$2){return $2.toUpperCase();}));
    				}
    				if(!polyphone) return result[0];
    				else return simpleUnique(result);
    			}
    		},
    		/**
    		 * 拼音转汉字,只支持单个汉字,返回所有匹配的汉字组合
    		 * @param pinyin 单个汉字的拼音,不能包含声调
    		 */
    		getHanzi: function(pinyin)
    		{
    			if(!dict.py2hz)
    			{
    				throw '抱歉,未找到合适的拼音字典文件!';
    			}
    			return dict.py2hz[pinyin] || '';
    		},
    		/**
    		 * 去除拼音中的声调,比如将 xiǎo míng tóng xué 转换成 xiao ming tong xue
    		 * @param pinyin 需要转换的拼音
    		 */
    		removeTone: function(pinyin)
    		{
    			var toneMap = 
    			{
    				"ā": "a1",
    				"á": "a2",
    				"ǎ": "a3",
    				"à": "a4",
    				"ō": "o1",
    				"ó": "o2",
    				"ǒ": "o3",
    				"ò": "o4",
    				"ē": "e1",
    				"é": "e2",
    				"ě": "e3",
    				"è": "e4",
    				"ī": "i1",
    				"í": "i2",
    				"ǐ": "i3",
    				"ì": "i4",
    				"ū": "u1",
    				"ú": "u2",
    				"ǔ": "u3",
    				"ù": "u4",
    				"ü": "v0",
    				"ǖ": "v1",
    				"ǘ": "v2",
    				"ǚ": "v3",
    				"ǜ": "v4",
    				"ń": "n2",
    				"ň": "n3",
    				"": "m2"
    			};
    			return pinyin.replace(/[āáǎàōóǒòēéěèīíǐìūúǔùüǖǘǚǜńň]/g, function(m){ return toneMap[m][0]; });
    		}
    	};
    
    
    	/**
    	 * 处理多音字,将类似['D', 'ZC', 'F']转换成['DZF', 'DCF']
    	 * 或者将 ['chang zhang', 'cheng'] 转换成 ['chang cheng', 'zhang cheng']
    	 */
    	function handlePolyphone(array, splitter, joinChar)
    	{
    		splitter = splitter || '';
    		var result = [''], temp = [];
    		for(var i=0; i<array.length; i++)
    		{
    			temp = [];
    			var t = array[i].split(splitter);
    			for(var j=0; j<t.length; j++)
    			{
    				for(var k=0; k<result.length; k++)
    					temp.push(result[k] + (result[k]?joinChar:'') + t[j]);
    			}
    			result = temp;
    		}
    		return simpleUnique(result);
    	}
    
    	/**
    	 * 根据词库找出多音字正确的读音
    	 * 这里只是非常简单的实现,效率和效果都有一些问题
    	 * 推荐使用第三方分词工具先对句子进行分词,然后再匹配多音字
    	 * @param chinese 需要转换的汉字
    	 * @param result 初步匹配出来的包含多个发音的拼音结果
    	 * @param splitter 返回结果拼接字符
    	 */
    	function parsePolyphone(chinese, result, splitter, withtone)
    	{
    		var poly = window.pinyin_dict_polyphone;
    		var max = 7; // 最多只考虑7个汉字的多音字词,虽然词库里面有10个字的,但是数量非常少,为了整体效率暂时忽略之
    		var temp = poly[chinese];
    		if(temp) // 如果直接找到了结果
    		{
    			temp = temp.split(' ');
    			for(var i=0; i<temp.length; i++)
    			{
    				result[i] = temp[i] || result[i];
    				if(!withtone) result[i] = pinyinUtil.removeTone(result[i]);
    			}
    			return result.join(splitter);
    		}
    		for(var i=0; i<chinese.length; i++)
    		{
    			temp = '';
    			for(var j=0; j<max && (i+j)<chinese.length; j++)
    			{
    				if(!/^[\u2E80-\u9FFF]+$/.test(chinese[i+j])) break; // 如果碰到非汉字直接停止本次查找
    				temp += chinese[i+j];
    				var res = poly[temp];
    				if(res) // 如果找到了多音字词语
    				{
    					res = res.split(' ');
    					for(var k=0; k<=j; k++)
    					{
    						if(res[k]) result[i+k] = withtone ? res[k] : pinyinUtil.removeTone(res[k]);
    					}
    					break;
    				}
    			}
    		}
    		// 最后这一步是为了防止出现词库里面也没有包含的多音字词语
    		for(var i=0; i<result.length; i++)
    		{
    			result[i] = result[i].replace(/ .*$/g, '');
    		}
    		return result.join(splitter);
    	}
    
    	// 简单数组去重
    	function simpleUnique(array)
    	{
    		var result = [];
    		var hash = {};
    		for(var i=0; i<array.length; i++)
    		{
    			var key = (typeof array[i]) + array[i];
    			if(!hash[key])
    			{
    				result.push(array[i]);
    				hash[key] = true;
    			}
    		}
    		return result;
    	}
    
    	pinyinUtil.parseDict();
    	pinyinUtil.dict = dict;
    	window.pinyinUtil = pinyinUtil;
    })();

     

    展开全文
  • 每天花30分钟就能赚10元钱的软件,你信吗?说实话小编之前听着,也感觉有点不可信,但世界总是充满惊喜的,所以抱着试试看的态度,去注册了,然后试玩,居然真的赚钱了。那么到底是一个什么样的软件这么神奇呢?它...
    每天花30分钟就能赚10元钱的软件,你信吗?说实话小编之前听着,也感觉有点不可信,但世界总是充满惊喜的,所以抱着试试看的态度,去注册了,然后试玩,居然真的赚钱了。那么到底是一个什么样的软件这么神奇呢?它就是让你越来越有钱的《人人转》赚钱软件。人人转联盟官网?人人转联盟是真的吗?人人转联盟能赚钱吗?你是不是也和小编一样感到困惑?贴心的小编已经自己先行注册**了,并且提现成功。下面就带着这些疑问,让小编为大家讲解一、二吧。
    


    第一、人人转联盟是真的吗?
    人人转联盟最近才出的一款以微信为载体的广告联盟平台,通过转发文章到朋友圈,按点击收款,点击一次商家就会产生一次费用,而微转联盟同样也是可以赚钱的,当你转发联盟文章,产生一个点击,就会有0.05元的佣金。朋友转发后产生的点击也算你的,不管转发多少次,都是你的。只要坚持做,从每天100个点击,到1万个点击,再到100万个点击只是时间的问题,只需要你每天花五分钟的时间,动动手指,转发文章。就能赚钱。
    这份工作非常适合上班族、在家全职妈妈、学生党等。利用空闲的时间转发到朋友圈信息就可以挣钱,现在是信息化时代,无论是什么形式的广告,都是按点击收费,你的每一次转发,都有可能会引来无数的人群转发点击。做这个的方法就是每天不停的加好友,好友越多,点击和转发的机率和人数就越大。这样你挣的就越多。






    1、人人转联盟注册入口http://66q.com/



    2、或者手机扫描二维码,进行注册!

    3、注册成功后、关注人人转联盟微信公众号


    4、点击“开始赚钱”





    5、分享文章





    6、查看收益



    第二、人人转联盟能赚钱吗?
    【提示】:我们强烈建议您在早上6:00-10:00之间分享,这个时段效果最佳。
    注册后点首页“开始赚钱”,打开后选择您喜欢的文章,然后分享到朋友圈、qq空间就可以了。有朋友阅读您的文章就会自动计费,每次阅读奖励0.05元。(小提示:如果您分享的文章被您的朋友分享了,他的好友里所产生的点击,也算进你的收入里。)


    为什么转发文章人人转联盟会给钱?

    ①您或许不知道:您的微信朋友圈、Q空间分享的内容都是有价值的,都是可以换得收益的,只是无人帮您开发,所以您无法从中获得收益;
    ②人人转联盟的出现,恰好解决了这个问题!人人转联盟内植入了广告,通过展示网页就可以获得广告收益。您只需要将我们的文章分享到您的朋友圈,就可以分成广告收益了;
    ③也就是说:我们想付费在您的朋友圈里展示文章,让您的朋友圈获到收益,您同意吗?这一切只须两步:1、注册成为人人转联盟的会员;2、在首页点“开始赚钱”,把获取的文章分享到朋友圈即可。然后,你就等着收益蹭蹭往上涨,躺着也赚钱的哦!


    100个好友如何才能月入万元?

    有一些人可能这样认为:我只有100个好友,反正赚不到多少钱,我就不参与了。其实不是这样的!推广在于日积月累,在于您是否用心。即使只有100个好友,每天业绩100万IP也不是没有可能。所以,您要认真看一下下述的方法:

    ①用心选择分享的内容。每个人都有不同的圈子,每个人的圈子都有不同的爱好内容,所以您一定要认真从微转联盟上查找适合您圈子的内容分享;只有您分享的内容是您的朋友喜欢的,他们才有可能转发。转发能让你的收益,倍增加速!从100到1万,再从1万到100万,也许只是分分钟的事!所以,您分享一个内容前,一定要想一下这个内容能不能让朋友们转发!

    ②留心您朋友在朋友圈里分享的内容。这些都是他们所喜欢的。只有懂得了朋友所喜欢的文章,您就可以从微转联盟里找一些相关的文章,这样的转发几率会大大提高哦!

    ③每天分享适当的条数。分享的条数不要太多,也不可太少。一般一天在5条左右,不超过12条;按照这样的方法尝试一下吧,您将会发现:刚开始您每天的业绩只有您好友的三分之一;一周后业绩增长到和好友数目一样多;再过一周即可达到好友数量的两倍;再过一段时间,您会突然发现您的业绩已经成了好友数量的N倍。原因是什么呢?就是因为您坚持每天在做,总有一些文章被人一次又一次的转载,而不管转载多少次,我们的系统都会计入您自己的业绩。这是个几何倍增的效果,每天做到100万IP绝对不是梦,这需要您用心去做!

    人人转联盟的收益有保障吗?

    微转联盟内广告由百度联盟**,收入稳定,安全可靠,请大家放心参与。

    微转联盟的佣金什么时候结算?

    在您申请提现后的3个工作日内,我们会把钱打到您申请提现时,所填写的支付宝内。

    加入需要什么条件吗?

    加入完全是免费的,只需要你有一部手机,有微信,申请成为转客以后关注微转联盟公众账号,转发上面文章即可。在微信上面即可完成提现。


    佣金什么时候结算?
    在您申请提现后的1个工作日内,我们会把钱打到您申请提现时,所填写的支付宝内。

    原文链接:http://www.bymseo.com/wangzhuan/144.html
    展开全文
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