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公开(公告)号：US09396723B2
公开(公告)日：2016-07-19
申请号：US14109845
申请日：2013-12-17
IPC: G10L15/00 , G10L15/06 , G06F17/28 , G10L15/183
CPC classification number: G10L15/063 , G06F17/28 , G10L15/183
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。
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公开(公告)号：US09818432B2
公开(公告)日：2017-11-14
申请号：US15176047
申请日：2016-06-07
Inventor： Lu Li , Jianxiong Ma , Li Lu
CPC classification number: G10L25/54 , G06F17/30026 , G10L15/14 , G10L21/10 , G10L2015/027 , G10L2015/088
Abstract: Methods and computer systems for audio search on a social networking platform are disclosed. The method includes: while running a social networking application, receiving a first audio input from a user of the computer system, the first audio input including one or more search keywords; generating a first audio confusion network from the first audio input; determining whether the first audio confusion network matches at least one of one or more second audio confusion networks, wherein a respective second audio confusion network was generated from a corresponding second audio input associated with a chat session of which the user is a participant; and identifying a second audio input corresponding to the at least one second audio confusion network that matches the first audio confusion network, wherein the identified second audio input includes the one or more search keywords that are included in the first audio input.
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公开(公告)号：US09811517B2
公开(公告)日：2017-11-07
申请号：US14148579
申请日：2014-01-06
Inventor： Haibo Liu , Eryu Wang , Xiang Zhang , Li Lu , Shuai Yue , Qiuge Liu , Bo Chen , Jian Liu , Lu Li
CPC classification number: G06F17/273 , G06F17/2775 , G06F17/2785 , G06F17/289 , G10L15/265
Abstract: A method of processing information content based on a Chinese language model is performed at a computer, the method including: identifying a plurality of expressions in the information content extracted from a speech input through speech recognition that is queued to be processed; dividing the expressions into a plurality of characteristic units according to semantic features and predetermined characteristics associated with each characteristic unit, each including a subset of the expressions and the predetermined characteristics at least including a respective integer number of expressions that are included in the characteristic unit; extracting, from the Chinese language model, a plurality of probabilities for punctuation marks associated with each characteristic unit; and in accordance with the probabilities, associating a respective punctuation mark with each characteristic unit included in the information content. The method further comprises adding punctuation marks based on a weight determined for each punctuation mark.
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公开(公告)号：US20160086609A1
公开(公告)日：2016-03-24
申请号：US14958606
申请日：2015-12-03
Inventor： Shuai Yue , Xiang Zhang , Li Lu , Feng Rao , Eryu Wang , Haibo Liu , Bo Chen , Jian Liu , Lu Li
CPC classification number: G10L17/24 , G06F3/167 , G10L15/22 , G10L17/02 , G10L17/16 , G10L17/26 , G10L2015/223
Abstract: The present application discloses a method, an electronic system and a non-transitory computer readable storage medium for recognizing audio commands in an electronic device. The electronic device obtains audio data based on an audio signal provided by a user and extracts characteristic audio fingerprint features from the audio data. The electronic device further determines whether the corresponding audio signal is generated by an authorized user by comparing the characteristic audio fingerprint features with an audio fingerprint model for the authorized user and with a universal background model that represents user-independent audio fingerprint features, respectively. When the corresponding audio signal is generated by the authorized user of the electronic device, an audio command is extracted from the audio data, and an operation is performed according to the audio command.
Abstract translation: 本申请公开了一种用于识别电子设备中的音频命令的方法，电子系统和非暂时性计算机可读存储介质。 电子设备基于由用户提供的音频信号获得音频数据，并从音频数据中提取特征音频指纹特征。 电子设备还通过将特征音频指纹特征与用于授权用户的音频指纹模型进行比较，以及分别表示用户独立的音频指纹特征的通用背景模型来确定对应的音频信号是否由授权用户产生。 当由电子设备的授权用户产生相应的音频信号时，从音频数据中提取音频命令，并根据音频命令进行操作。
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5.发明授权Keyword detection with international phonetic alphabet by foreground model and background model 有权用前景模型和背景模型对国际语音字母进行关键词检测公开(公告)号：US09466289B2
公开(公告)日：2016-10-11
申请号：US14103775
申请日：2013-12-11
CPC classification number: G10L15/063 , G10L15/08 , G10L2015/088
Abstract: An electronic device with one or more processors and memory trains an acoustic model with an international phonetic alphabet (IPA) phoneme mapping collection and audio samples in different languages, where the acoustic model includes: a foreground model; and a background model. The device generates a phone decoder based on the trained acoustic model. The device collects keyword audio samples, decodes the keyword audio samples with the phone decoder to generate phoneme sequence candidates, and selects a keyword phoneme sequence from the phoneme sequence candidates. After obtaining the keyword phoneme sequence, the device detects one or more keywords in an input audio signal with the trained acoustic model, including: matching phonemic keyword portions of the input audio signal with phonemes in the keyword phoneme sequence with the foreground model; and filtering out phonemic non-keyword portions of the input audio signal with the background model.
Abstract translation: 具有一个或多个处理器和存储器的电子设备具有使用不同语言的国际语音字母（IPA）音素映射收集和音频样本的声学模型，其中声学模型包括：前景模型; 和背景模型。 该设备基于经过训练的声学模型生成电话解码器。 设备收集关键字音频样本，用手机解码器解码关键词音频样本，以产生音素序列候选，并从音素序列候选中选择关键词音素序列。 在获得关键字音素序列之后，设备利用经训练的声学模型检测输入音频信号中的一个或多个关键词，包括：使用前景模型将关键字音素序列中的输入音频信号的音素关键词部分与音素相匹配; 并用背景模型滤出输入音频信号的音素非关键字部分。
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Patent Agency Ranking
公开(公告)号：US10453477B2
公开(公告)日：2019-10-22
申请号：US15728464
申请日：2017-10-09
Inventor： Lu Li , Jianxiong Ma , Li Lu
Abstract: Methods and computer systems for audio search on a social networking platform are disclosed. While running a social networking application, a computer system receives a first audio input from a user of the computer system and then generates a first audio confusion network from the first audio input. After comparing the first audio confusion network with one or more second audio confusion networks, each corresponding to a second audio input associated with one of a plurality of participants of a chat session of the social networking application, the computer system identifies at least one second audio input corresponding to the at least one second audio confusion network that matches the first audio confusion network and displays a portion of the chat session including a visual icon representing the identified second audio input on a display of the computer system.
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公开(公告)号：US09779728B2
公开(公告)日：2017-10-03
申请号：US14160808
申请日：2014-01-22
IPC: G10L15/00 , G10L15/04 , G10L15/18 , G10L15/26 , G10L15/187 , G06F17/27 , G10L15/183
CPC classification number: G10L15/1815 , G06F17/27 , G06F17/2725 , G10L15/04 , G10L15/183 , G10L15/187 , G10L15/26 , G10L15/265
Abstract: Systems and methods are provided for adding punctuations. For example, one or more first feature units are identified in a voice file taken as a whole; the voice file is divided into multiple segments by detecting silences in the voice file; one or more second feature units are identified in the voice file; a first aggregate weight of first punctuation states of the voice file and a second aggregate weight of second punctuation states of the voice file are determined, using a language model established based on word separation and third semantic features; a weighted calculation is performed to generate a third aggregate weight based on a linear combination associated with the first aggregate weight and the second aggregate weight; and one or more final punctuations are added to the voice file based on at least information associated with the third aggregate weight.
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公开(公告)号：US09355637B2
公开(公告)日：2016-05-31
申请号：US14620000
申请日：2015-02-11
Inventor： Jianxiong Ma , Lu Li , Li Lu , Xiang Zhang , Shuai Yue , Feng Rao , Eryu Wang , Linghui Kong
CPC classification number: G10L15/18 , G10L15/08 , G10L15/28 , G10L15/32 , G10L2015/088
Abstract: A method and an apparatus are provided for retrieving keyword. The apparatus configures at least two types of language models in a model file, where each type of language model includes a recognition model and a corresponding decoding model; the apparatus extracts a speech feature from the to-be-processed speech data; performs language matching on the extracted speech feature by using recognition models in the model file one by one, and determines a recognition model based on a language matching rate; and determines a decoding model corresponding to the recognition model; decoding the extracted speech feature by using the determined decoding model, and obtains a word recognition result after the decoding; and matches a keyword in a keyword dictionary and the word recognition result, and outputs a matched keyword.
Abstract translation: 提供了一种用于检索关键字的方法和装置。 该装置在模型文件中配置至少两种类型的语言模型，其中每种类型的语言模型包括识别模型和相应的解码模型; 该设备从待处理语音数据中提取语音特征; 通过在模型文件中逐一使用识别模型对提取出的语音特征进行语言匹配，并根据语言匹配率确定识别模型; 并确定与识别模型相对应的解码模型; 通过使用所确定的解码模型来解码所提取的语音特征，并且在解码之后获得字识别结果; 并且将关键词字典中的关键字与单词识别结果进行匹配，并输出匹配的关键字。
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公开(公告)号：US09257118B2
公开(公告)日：2016-02-09
申请号：US14620000
申请日：2015-02-11
Inventor： Jianxiong Ma , Lu Li , Li Lu , Xiang Zhang , Shuai Yue , Feng Rao , Eryu Wang , Linghui Kong
Abstract: A method and an apparatus are provided for retrieving keyword. The apparatus configures at least two types of language models in a model file, where each type of language model includes a recognition model and a corresponding decoding model; the apparatus extracts a speech feature from the to-be-processed speech data; performs language matching on the extracted speech feature by using recognition models in the model file one by one, and determines a recognition model based on a language matching rate; and determines a decoding model corresponding to the recognition model; decoding the extracted speech feature by using the determined decoding model, and obtains a word recognition result after the decoding; and matches a keyword in a keyword dictionary and the word recognition result, and outputs a matched keyword.
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公开(公告)号：US20140358539A1
公开(公告)日：2014-12-04
申请号：US14181263
申请日：2014-02-14
IPC: G10L15/06
CPC classification number: G10L15/063 , G10L15/183 , G10L15/197
Abstract: A method includes: acquiring data samples; performing categorized sentence mining in the acquired data samples to obtain categorized training samples for multiple categories; building a text classifier based on the categorized training samples; classifying the data samples using the text classifier to obtain a class vocabulary and a corpus for each category; mining the corpus for each category according to the class vocabulary for the category to obtain a respective set of high-frequency language templates; training on the templates for each category to obtain a template-based language model for the category; training on the corpus for each category to obtain a class-based language model for the category; training on the class vocabulary for each category to obtain a lexicon-based language model for the category; building a speech decoder according to an acoustic model, the class-based language model and the lexicon-based language model for any given field, and the data samples.
Abstract translation: 一种方法包括：获取数据样本; 在获取的数据样本中执行分类句子挖掘以获得用于多个类别的分类训练样本; 基于分类训练样本构建文本分类器; 使用文本分类器对数据样本进行分类，以获得每个类别的类词汇和语料库; 根据类别的词汇量挖掘每个类别的语料库，以获得相应的一组高频语言模板; 对每个类别的模板进行培训，以获取该类别的基于模板的语言模型; 对每个类别的语料库进行训练，以获得该类别的基于类的语言模型; 对每个类别的课堂词汇进行培训，以获得该类别的基于词典的语言模型; 根据声学模型，基于类的语言模型和任何给定字段的基于词典的语言模型构建语音解码器，以及数据样本。
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