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公开(公告)号：US20160057099A1
公开(公告)日：2016-02-25
申请号：US14932233
申请日：2015-11-04
Applicant: Google Inc.
Inventor： Brian Patrick Strope , Francoise Beaufays , Hy Murveit
CPC classification number: H04L61/106 , H04L12/66 , H04L51/28 , H04L51/32 , H04L51/36 , H04M1/7255 , H04M3/42102 , H04W4/16 , H04W8/183
Abstract: In one implementation a computer-implemented method includes generating a group of telephone contacts for a first user, wherein the generating includes identifying a second user as a contact of the first user based upon a determination that the second user has at least a threshold email-based association with the first user; and adding the identified second user to the group of telephone contacts for the first user. The method further includes receiving a first request to connect a first telephone device associated with the first user to a second telephone device associated with the second user. The method also includes identifying a contact identifier of the second telephone device using the generated group of telephone contacts for the first user, and initiating a connection between the first telephone device and the second telephone device using the identified contact identifier.
Abstract translation: 在一个实现中，计算机实现的方法包括为第一用户生成一组电话联系人，其中生成包括基于第二用户至少具有阈值电子邮件地址的确定来将第二用户识别为第一用户的联系人， 与第一个用户的关联; 以及将所识别的第二用户添加到第一用户的电话联系人组。 该方法还包括接收将与第一用户相关联的第一电话设备连接到与第二用户相关联的第二电话设备的第一请求。 该方法还包括使用生成的第一用户的电话联系人识别第二电话设备的联系人标识符，以及使用所识别的联系人标识符来启动第一电话设备和第二电话设备之间的连接。
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Patent Agency Ranking
公开(公告)号：US20160275951A1
公开(公告)日：2016-09-22
申请号：US15171374
申请日：2016-06-02
Applicant: Google Inc.
Inventor： Brian Patrick Strope , Francoise Beaufays , Olivier Siohan
Abstract: The subject matter of this specification can be embodied in, among other things, a method that includes receiving an audio signal and initiating speech recognition tasks by a plurality of speech recognition systems (SRS's). Each SRS is configured to generate a recognition result specifying possible speech included in the audio signal and a confidence value indicating a confidence in a correctness of the speech result. The method also includes completing a portion of the speech recognition tasks including generating one or more recognition results and one or more confidence values for the one or more recognition results, determining whether the one or more confidence values meets a confidence threshold, aborting a remaining portion of the speech recognition tasks for SRS's that have not generated a recognition result, and outputting a final recognition result based on at least one of the generated one or more speech results.
Abstract translation: 除了别的以外，本说明书的主题可以体现在包括通过多个语音识别系统（SRS）接收音频信号和发起语音识别任务的方法。 每个SRS被配置为产生指定包括在音频信号中的可能语音的识别结果，以及指示对语音结果的正确性置信度的置信度值。 该方法还包括完成语音识别任务的一部分，包括生成一个或多个识别结果和一个或多个识别结果的一个或多个置信度值，确定一个或多个置信度值是否满足置信阈值，中止其余部分 的没有产生识别结果的SRS的语音识别任务，并且基于所生成的一个或多个语音结果中的至少一个来输出最终识别结果。
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公开(公告)号：US20150170642A1
公开(公告)日：2015-06-18
申请号：US14109316
申请日：2013-12-17
Applicant: Google Inc.
Inventor： Fuchun Peng , Francoise Beaufays , Pedro J. Moreno Mengibar , Brian Patrick Strope
IPC: G10L15/187 , G10L15/26
CPC classification number: G10L15/187 , G10L15/005 , G10L2015/025 , G10L2015/227
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, including selecting terms; obtaining an expected phonetic transcription of an idealized native speaker of a natural language speaking the terms; receiving audio data corresponding to a particular user speaking the terms in the natural language; obtaining, based on the audio data, an actual phonetic transcription of the particular user speaking the terms in the natural language; aligning the expected phonetic transcription of the idealized native speaker of the natural language with the actual phonetic transcription of the particular user; identifying, based on the aligning, a portion of the expected phonetic transcription that is different than a corresponding portion of the actual phonetic transcription; and based on identifying the portion of the expected phonetic transcription, designating the expected phonetic transcription as a substitute pronunciation for the corresponding portion of the actual phonetic transcription.
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，包括选择术语; 用语言来获得理想化的母语者自然语言的预期语音转录; 接收对应于以自然语言表达术语的特定用户的音频数据; 基于音频数据获得以自然语言表达术语的特定用户的实际语音转录; 将理想化的自然语言的母语者的预期语音转录与特定用户的实际语音转录对齐; 基于对齐来识别不同于实际语音转录的相应部分的预期语音转录的一部分; 并且基于识别预期语音转录的部分，将预期的语音转录指定为实际语音转录的相应部分的替代发音。
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公开(公告)号：US09747897B2
公开(公告)日：2017-08-29
申请号：US14109316
申请日：2013-12-17
Applicant: Google Inc.
Inventor： Fuchun Peng , Francoise Beaufays , Pedro J. Moreno Mengibar , Brian Patrick Strope
IPC: G10L15/28 , G10L15/187 , G10L15/00 , G10L15/22 , G10L15/02
CPC classification number: G10L15/187 , G10L15/005 , G10L2015/025 , G10L2015/227
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, including selecting terms; obtaining an expected phonetic transcription of an idealized native speaker of a natural language speaking the terms; receiving audio data corresponding to a particular user speaking the terms in the natural language; obtaining, based on the audio data, an actual phonetic transcription of the particular user speaking the terms in the natural language; aligning the expected phonetic transcription of the idealized native speaker of the natural language with the actual phonetic transcription of the particular user; identifying, based on the aligning, a portion of the expected phonetic transcription that is different than a corresponding portion of the actual phonetic transcription; and based on identifying the portion of the expected phonetic transcription, designating the expected phonetic transcription as a substitute pronunciation for the corresponding portion of the actual phonetic transcription.
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公开(公告)号：US20170039174A1
公开(公告)日：2017-02-09
申请号：US15229743
申请日：2016-08-05
Applicant: Google Inc.
Inventor： Brian Patrick Strope , Matthew Steedman Henderson
CPC classification number: G06F17/2264 , G06F17/24 , G06F17/274 , G06F17/28 , G06F17/30705 , G06N3/0454 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for transforming and classifying text based on analysis of training texts from particular authors. One of the methods includes receiving an input text including one or more words and a requested author; generating a vector stream representing the input text based on an encoder language model and including one or more multi-dimensional vectors associated with associated words of the words of the input text and representing a distribution of contexts in which the associated words occurred in a plurality of training texts; and producing an output text representing a particular transformation of the input text based at least in part on a decoder language model, the generated vector stream, and the requested author.
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，用于基于来自特定作者的训练文本的分析来转换和分类文本。 其中一种方法包括接收包括一个或多个单词的输入文本和所请求的作者; 基于编码器语言模型生成表示输入文本的向量流，并且包括与输入文本的单词的关联词相关联的一个或多个多维向量，并且表示在多个 训练文本; 以及至少部分地基于解码器语言模型，所生成的向量流和所请求的作者来产生表示输入文本的特定变换的输出文本。
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公开(公告)号：US09858917B1
公开(公告)日：2018-01-02
申请号：US15013471
申请日：2016-02-02
Applicant: Google Inc.
Inventor： Brian Patrick Strope , Douglas H. Beeferman
CPC classification number: G10L15/01 , G10L15/065 , G10L15/07 , G10L15/10 , G10L17/02
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enhancing speech recognition accuracy. In one aspect, a method includes receiving voice queries, obtaining, for one or more of the voice queries, feedback information that references an action taken by a user that submitted the voice query after reviewing a result of the voice query, generating, for the one or more voice queries, a posterior recognition confidence measure that reflects a probability that the voice query was correctly recognized, wherein the posterior recognition confidence measure is generated based at least on the feedback information for the voice query, selecting a subset of the one or more voice queries based on the posterior recognition confidence measures, and adapting an acoustic model using the subset of the voice queries.
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