公开(公告)号：WO2014117583A1

公开(公告)日：2014-08-07

申请号：PCT/CN2013/087994

申请日：2013-11-28

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： ZHANG, Xiang ,  LU, Li ,  WANG, Eryu ,  YUE, Shuai ,  RAO, Feng ,  LIU, Haibo ,  LI, Lou ,  LU, Duling ,  CHEN, Bo

IPC: H04L9/32

CPC classification number: G06F21/32 ,  G06F2221/2117

Abstract: A computer-implemented method is performed at a server having one or more processors and memory storing programs executed by the one or more processors for authenticating a user from video and audio data. The method includes: receiving a login request from a mobile device, the login request including video data and audio data; extracting a group of facial features from the video data; extracting a group of audio features from the audio data and recognizing a sequence of words in the audio data; identifying a first user account whose respective facial features match the group of facial features and a second user account whose respective audio features match the group of audio features. If the first user account is the same as the second user account, retrieve the sequence of words associated with the user account and compare the sequences of words for authentication purpose.

Abstract translation: 在具有一个或多个处理器的服务器和由一个或多个处理器执行的用于从视频和音频数据认证用户的存储器存储程序的服务器执行计算机实现的方法。 该方法包括：从移动设备接收登录请求，登录请求包括视频数据和音频数据; 从视频数据中提取一组面部特征; 从音频数据提取一组音频特征并识别音频数据中的单词序列; 识别其各自的面部特征与该组面部特征相匹配的第一用户帐户和其各个音频特征与该组音频特征相匹配的第二用户帐户。 如果第一个用户帐户与第二个用户帐户相同，则检索与用户帐户相关联的单词序列，并比较用于验证目的的单词序列。

公开(公告)号：WO2014117549A1

公开(公告)日：2014-08-07

申请号：PCT/CN2013/086152

申请日：2013-10-29

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： LI, Lou ,  CHENG, Qiang ,  RAO, Feng ,  LU, Li ,  ZHANG, Xiang ,  YUE, Shuai ,  CHEN, Bo ,  LU, Duling

IPC: G06F17/27

CPC classification number: G06F17/273 ,  G06F17/2775

Abstract: A computer-implemented method is performed at a device having one or more processors and memory storing programs executed by the one or more processors. The method comprises: selecting a target word in a target sentence; from the target sentence, acquiring a first sequence of words that precede the target word and a second sequence of words that succeed the target word; from a sentence database, searching and acquiring a group of words, each of which separates the first sequence of words from the second sequence of words in a sentence; creating a candidate sentence for each of the candidate words by replacing the target word in the target sentence with each of the candidate words; determining the fittest sentence among the candidate sentences according to a linguistic model; and suggesting the candidate word within the fittest sentence as a correction.

Abstract translation: 在具有一个或多个处理器的设备和由一个或多个处理器执行的存储器存储程序的设备上执行计算机实现的方法。 该方法包括：在目标句子中选择目标词; 从所述目标句子中获取所述目标词之前的第一个单词序列以及继续所述目标单词的第二个单词序列; 从句子数据库中搜索并获取一组单词，每一个单词都将第一个单词序列与一个句子中的第二个单词序列进行分隔; 通过用目标句子中的每个候选词替换目标词来为每个候选词创建候选句子; 根据语言模型确定候选句子中最适合的句子; 并建议适者生词中的候选词作为校正。

公开(公告)号：WO2014117548A1

公开(公告)日：2014-08-07

申请号：PCT/CN2013/085948

申请日：2013-10-25

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： LU, Duling ,  LI, Lu ,  RAO, Feng ,  CHEN, Bo ,  LU, Li ,  ZHANG, Xiang ,  WANG, Eryu ,  YUE, Shuai

IPC: G10L15/06

CPC classification number: G10L15/063 ,  G10L15/05 ,  G10L2015/0631

Abstract: A method and a device for training an acoustic language model, include: conducting word segmentation for training samples in a training corpus using an initial language model containing no word class labels, to obtain initial word segmentation data containing no word class labels; performing word class replacement for the initial word segmentation data containing no word class labels, to obtain first word segmentation data containing word class labels; using the first word segmentation data containing word class labels to train a first language model containing word class labels; using the first language model containing word class labels to conduct word segmentation for the training samples in the training corpus, to obtain second word segmentation data containing word class labels; and in accordance with the second word segmentation data meeting one or more predetermined criteria, using the second word segmentation data containing word class labels to train the acoustic language model.

Abstract translation: 一种用于训练声学语言模型的方法和装置，包括：使用不含词类标签的初始语言模型，在训练语料库中训练样本的词分割，以获得不包含词类标签的初始分词数据; 对不包含词类标签的初始分词数据执行单词类替换，以获得包含单词分类标签的第一分词数据; 使用包含词类标签的第一词分割数据来训练包含词类标签的第一语言模型; 使用包含词类标签的第一语言模型对训练语料库中的训练样本进行词分割，以获得包含词类标签的第二词分割数据; 并且根据满足一个或多个预定标准的第二字分割数据，使用包含词类标签的第二词分割数据来训练声学语言模型。

公开(公告)号：WO2014114117A1

公开(公告)日：2014-07-31

申请号：PCT/CN2013/085926

申请日：2013-10-25

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： LI, Lu ,  CHENG, Qiang ,  MA, Jianxiong ,  RAO, Feng ,  LU, Duling ,  LU, Li ,  ZHANG, Xiang ,  CHEN, Bo

IPC: G06F17/27

CPC classification number: G06F17/2735 ,  G06F17/2863

Abstract: A method is implemented at a computer to determine that certain information content is composed or compiled in a specific language selected among two or more similar languages. The computer integrates a first vocabulary list of a first language and a second vocabulary list of a second language into a comprehensive vocabulary list. The integrating includes analyzing the first vocabulary list in view of the second vocabulary list to identify a first vocabulary sub-list that is used in the first language, but not in the second language. The computer then identifies, in the information content, a plurality of expressions that are included in the comprehensive vocabulary list, and a subset of expressions that are included in the first vocabulary sub-list. Upon a determination that a total frequency of occurrence of the subset of expressions meets predetermined occurrence criteria, the computer determines that the information content is composed in the first language.

Abstract translation: 在计算机上实现一种方法，以确定某些信息内容是以两种或多种类似语言中选择的特定语言构成或编译的。 计算机将第一语言的第一词汇列表和第二语言的第二词汇列表集成到综合词汇列表中。 该集成包括根据第二词汇列表分析第一词汇列表以识别在第一语言中使用的第一词汇子列表，而不是第二语言。 然后，计算机在信息内容中识别包括在综合词汇列表中的多个表达式以及包括在第一词汇子列表中的表达式的子集。 在确定表达子集的总出现频率满足预定出现标准的情况下，计算机确定信息内容以第一语言组成。

公开(公告)号：WO2014117555A1

公开(公告)日：2014-08-07

申请号：PCT/CN2013/086707

申请日：2013-11-07

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： RAO, Feng ,  LU, Li ,  CHEN, Bo ,  YUE, Shuai ,  ZHANG, Xiang ,  WANG, Eryu ,  XIE, Dadong ,  LI, Lou ,  LU, Duling

IPC: G10L15/00 ,  G10L15/02 ,  G10L15/14 ,  G10L15/22 ,  G10L15/26

CPC classification number: G10L15/197

Abstract: An automatic speech recognition method includes at a computer having one or more processors and a memory for storing one or more programs to be executed by the processors, obtaining a plurality of speech corpus categories through classifying and calculating raw speech corpus (801); obtaining a plurality of classified language models that respectively correspond to the plurality of speech corpus categories through language model training applied on each speech corpus category (802); obtaining an interpolation language model through implementing a weighted interpolation on each classified language model and merging the interpolated plurality of classified language models (803); constructing a decoding resource in accordance with an acoustic model and the interpolation language model (804); decoding input speech using the decoding resource, and outputting a character string with a highest probability as the recognition result of the input speech (805).

Abstract translation: 自动语音识别方法包括在具有一个或多个处理器的计算机和用于存储要由处理器执行的一个或多个程序的存储器，通过分类和计算原始语音语料库（801）获得多个语音语料库类别; 通过在每个语音语料库类别（802）上应用的语言模型训练获得分别对应于多个语音语料库类别的多个分类语言模型; 通过对每个分类语言模型实施加权内插并合并内插多个分类语言模型（803）来获得内插语言模型; 根据声学模型和内插语言模型构造解码资源（804）; 使用解码资源解码输入语音，并输出具有最高概率的字符串作为输入语音的识别结果（805）。

公开(公告)号：WO2014114116A1

公开(公告)日：2014-07-31

申请号：PCT/CN2013/085735

申请日：2013-10-23

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： WANG, Eryu ,  LU, Li ,  ZHANG, Xiang ,  LIU, Haibo ,  LI, Lou ,  RAO, Feng ,  LU, Duling ,  YUE, Shuai ,  CHEN, Bo

IPC: G10L17/20

CPC classification number: G10L17/18

Abstract: A method and system (800) for voiceprint recognition, include: establishing a first-level Deep Neural Network (DNN) model based on unlabeled speech data, the unlabeled speech data containing no speaker labels and the first-level DNN model specifying a plurality of basic voiceprint features for the unlabeled speech data; obtaining a plurality of high-level voiceprint features by tuning the first-level DNN model based on labeled speech data, the labeled speech data containing speech samples with respective speaker labels, and the tuning producing a second-level DNN model specifying the plurality of high-level voiceprint features; based on the second-level DNN model, registering a respective high-level voiceprint feature sequence for a user based on a registration speech sample received from the user; and performing speaker verification for the user based on the respective high-level voiceprint feature sequence registered for the user.

Abstract translation: 一种用于声纹识别的方法和系统（800）包括：基于未标记的语音数据建立第一级深神经网络（DNN）模型，不包含扬声器标签的未标记语音数据和指定多个 用于未标记语音数据的基本声纹特征; 通过基于标记的语音数据调整第一级DNN模型来获得多个高级声纹特征，所述标记语音数据包含具有相应扬声器标签的语音样本，并且调谐产生指定多个高的DNN模型 级的声纹特征; 基于第二级DNN模型，基于从用户接收到的注册语音样本，为用户注册相应的高级声纹特征序列; 并且基于为用户注册的各个高级声纹特征序列对用户执行说话人验证。