Multiple recognizer speech recognition
    1.
    发明授权
    Multiple recognizer speech recognition 有权
    多重识别语音识别

    公开(公告)号:US09058805B2

    公开(公告)日:2015-06-16

    申请号:US13892590

    申请日:2013-05-13

    Applicant: Google Inc.

    Abstract: The subject matter of this specification can be embodied in, among other things, a method that includes receiving audio data that corresponds to an utterance, obtaining a first transcription of the utterance that was generated using a limited speech recognizer. The limited speech recognizer includes a speech recognizer that includes a language model that is trained over a limited speech recognition vocabulary that includes one or more terms from a voice command grammar, but that includes fewer than all terms of an expanded grammar. A second transcription of the utterance is obtained that was generated using an expanded speech recognizer. The expanded speech recognizer includes a speech recognizer that includes a language model that is trained over an expanded speech recognition vocabulary that includes all of the terms of the expanded grammar. The utterance is classified based at least on a portion of the first transcription or the second transcription.

    Abstract translation: 本说明书的主题可以包括接收对应于话语的音频数据的方法,获得使用有限语音识别器产生的话语的第一次转录。 有限语音识别器包括语音识别器,该语音识别器包括一个语言模型,该语言模型通过有限的语音识别词汇训练,该语义识别词汇包括来自语音命令语法的一个或多个术语,但是包括扩展语法的全部术语。 获得了使用扩展语音识别器生成的话语的第二个转录。 扩展语音识别器包括语音识别器,其包括在包括扩展语法的所有术语的扩展语音识别词汇训练的语言模型。 该话语至少基于第一转录或第二转录的一部分进行分类。

    Increasing semantic coverage with semantically irrelevant insertions

    公开(公告)号:US09020809B1

    公开(公告)日:2015-04-28

    申请号:US13780804

    申请日:2013-02-28

    Applicant: Google Inc.

    CPC classification number: G10L15/063 G06F17/2785 G10L15/19 G10L2015/0631

    Abstract: A method includes accessing data specifying a set of actions, each action defining a user device operation and for each action: accessing a corresponding set of command sentences for the action, determining first n-grams in the set of command sentences that are semantically relevant for the action, determining second n-grams in the set of command sentences that are semantically irrelevant for the action, generating a training set of command sentences from the corresponding set of command sentences, the generating the training set of command sentences including removing each second n-gram from each sentence in the corresponding set of command sentences for the action, and generating a command model from the training set of command sentences configured to generate an action score for the action for an input sentence based on: first n-grams for the action, and second n-grams for the action that are also second n-grams for all other actions.

    Utterance selection for automated speech recognizer training
    3.
    发明授权
    Utterance selection for automated speech recognizer training 有权
    自动语音识别器培训的话语选择

    公开(公告)号:US09263033B2

    公开(公告)日:2016-02-16

    申请号:US14314295

    申请日:2014-06-25

    Applicant: Google Inc.

    CPC classification number: G10L15/063 G10L2015/0635

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a set of training utterances. The methods, systems, and apparatus include actions of obtaining a target multi-dimensional distribution of characteristics in an initial set of candidate utterances and selecting a subset of the initial set of candidate utterances based on speech recognition confidence scores associated with the candidate utterances. Additional actions include selecting a particular candidate utterance from the subset of the initial set of utterances and determining that adding the particular candidate utterance to a set of training utterances reduces a divergence of a multi-dimensional distribution of the characteristics in the set of training utterances from the target multi-dimensional distribution. Further actions include adding the particular candidate utterance to the set of training utterances.

    Abstract translation: 方法,系统和装置,包括在计算机存储介质上编码的计算机程序,用于产生一组训练话语。 方法,系统和装置包括在初始的候选话语集中获得特征的目标多维分布的动作,并且基于与候选话语相关联的语音识别置信度得分来选择候选话语的初始集合的子集。 附加动作包括从初始话语集合的子集中选择特定的候选话语,并确定将特定候选话语添加到一组训练话语中减少了训练语言组中的特征的多维分布的发散, 目标多维分布。 进一步的行动包括将特定候选人的话语添加到一组训练话语中。

    Dictionary filtering using market data
    4.
    发明授权
    Dictionary filtering using market data 有权
    使用市场数据进行字典过滤

    公开(公告)号:US08473293B1

    公开(公告)日:2013-06-25

    申请号:US13658139

    申请日:2012-10-23

    Applicant: Google Inc.

    CPC classification number: G10L15/06

    Abstract: This specification describes technologies relating to system, methods, and articles for updating a speech recognition dictionary based on, at least in part, both search query and market data metrics. In general, one innovative aspect of the subject matter described in this specification can be embodied in a method comprising (i) identifying a candidate term for possible inclusion in a speech recognition dictionary, (ii) identifying at least one search query metric associated with the identified candidate term, (iii) identifying at least one market data metric associated with the identified candidate term, and (iv) generating a candidate term score for the identified candidate term based, at least in part, on a weighted combination of the at least one identified search query metric and the at least one identified market data metric.

    Abstract translation: 本说明书描述了至少部分地基于搜索查询和市场数据度量的用于更新语音识别词典的系统,方法和文章的技术。 通常,本说明书中描述的主题的一个创新方面可以体现在一种方法中,该方法包括:(i)识别可能包括在语音识别词典中的候选词,(ii)识别至少一个与 确定候选词,(iii)识别与所识别的候选词相关联的至少一个市场数据度量,以及(iv)至少部分地至少基于所述候选词的加权组合生成所识别的候选词的候选词分数 一个确定的搜索查询度量和至少一个确定的市场数据量度。

    Context-based speech recognition
    5.
    发明授权
    Context-based speech recognition 有权
    基于语境的语音识别

    公开(公告)号:US09311915B2

    公开(公告)日:2016-04-12

    申请号:US14030265

    申请日:2013-09-18

    Applicant: Google Inc.

    CPC classification number: G10L15/16

    Abstract: A processing system receives an audio signal encoding a portion of an utterance. The processing system receives context information associated with the utterance, wherein the context information is not derived from the audio signal or any other audio signal. The processing system provides, as input to a neural network, data corresponding to the audio signal and the context information, and generates a transcription for the utterance based on at least an output of the neural network.

    Abstract translation: 处理系统接收编码话音的一部分的音频信号。 处理系统接收与话语相关联的上下文信息,其中上下文信息不是从音频信号或任何其它音频信号导出的。 处理系统作为神经网络的输入提供对应于音频信号和上下文信息的数据,并且基于至少神经网络的输出来产生用于话语的转录。

    UTTERANCE SELECTION FOR AUTOMATED SPEECH RECOGNIZER TRAINING
    6.
    发明申请
    UTTERANCE SELECTION FOR AUTOMATED SPEECH RECOGNIZER TRAINING 有权
    自动选择语音识别器培训

    公开(公告)号:US20150379983A1

    公开(公告)日:2015-12-31

    申请号:US14314295

    申请日:2014-06-25

    Applicant: Google Inc.

    CPC classification number: G10L15/063 G10L2015/0635

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a set of training utterances. The methods, systems, and apparatus include actions of obtaining a target multi-dimensional distribution of characteristics in an initial set of candidate utterances and selecting a subset of the initial set of candidate utterances based on speech recognition confidence scores associated with the candidate utterances. Additional actions include selecting a particular candidate utterance from the subset of the initial set of utterances and determining that adding the particular candidate utterance to a set of training utterances reduces a divergence of a multi-dimensional distribution of the characteristics in the set of training utterances from the target multi-dimensional distribution. Further actions include adding the particular candidate utterance to the set of training utterances.

    Abstract translation: 方法,系统和装置,包括在计算机存储介质上编码的计算机程序,用于产生一组训练话语。 方法,系统和装置包括在初始的候选话语集中获得特征的目标多维分布的动作,并且基于与候选话语相关联的语音识别置信度得分来选择候选话语的初始集合的子集。 附加动作包括从初始话语集合的子集中选择特定的候选话语,并确定将特定候选话语添加到一组训练话语中减少了训练语言组中的特征的多维分布的发散, 目标多维分布。 进一步的行动包括将特定候选人的话语添加到一组训练话语中。

    Bootstrapping named entity canonicalizers from English using alignment models
    7.
    发明授权
    Bootstrapping named entity canonicalizers from English using alignment models 有权
    使用对齐模型从英文引导命名实体规范化

    公开(公告)号:US09146919B2

    公开(公告)日:2015-09-29

    申请号:US13830969

    申请日:2013-03-14

    Applicant: Google Inc.

    CPC classification number: G06F17/289 G06F17/278 G06F17/28

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training recognition canonical representations corresponding to named-entity phrases in a second natural language based on translating a set of allowable expressions with canonical representations from a first natural language, which may be generated by expanding a context-free grammar for the allowable expressions for the first natural language.

    Abstract translation: 方法,系统和装置,包括在计算机存储介质上编码的计算机程序,用于训练对应于第二自然语言中的命名实体短语的识别规范表示,其基于从第一自然语言的规范表示转换一组可允许表达, 这可以通过扩展第一自然语言的允许表达式的上下文无关语法来产生。

    BOOTSTRAPPING NAMED ENTITY CANONICALIZERS FROM ENGLISH USING ALIGNMENT MODELS
    8.
    发明申请
    BOOTSTRAPPING NAMED ENTITY CANONICALIZERS FROM ENGLISH USING ALIGNMENT MODELS 有权
    使用对齐模型从英文引用名词实体

    公开(公告)号:US20140200876A1

    公开(公告)日:2014-07-17

    申请号:US13830969

    申请日:2013-03-14

    Applicant: Google Inc.

    CPC classification number: G06F17/289 G06F17/278 G06F17/28

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training recognition canonical representations corresponding to named-entity phrases in a second natural language based on translating a set of allowable expressions with canonical representations from a first natural language, which may be generated by expanding a context-free grammar for the allowable expressions for the first natural language.

    Abstract translation: 方法,系统和装置,包括在计算机存储介质上编码的计算机程序,用于训练对应于第二自然语言中的命名实体短语的识别规范表示,其基于从第一自然语言的规范表示转换一组可允许表达, 这可以通过扩展第一自然语言的允许表达式的上下文无关语法来产生。

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