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1. 发明申请

US20100076765A1 STRUCTURED MODELS OF REPITITION FOR SPEECH RECOGNITION 有权
标题翻译：用于语音识别的结构化复制模型
公开(公告)号：US20100076765A1
公开(公告)日：2010-03-25
申请号：US12233826
申请日：2008-09-19
申请人： Geoffrey G. Zweig , Xiao Li , Dan Bohus , Alejandro Acero , Eric J. Horvitz
发明人： Geoffrey G. Zweig , Xiao Li , Dan Bohus , Alejandro Acero , Eric J. Horvitz
IPC分类号： G10L15/00
CPC分类号： G10L15/1822
摘要： Described is a technology by which a structured model of repetition is used to determine the words spoken by a user, and/or a corresponding database entry, based in part on a prior utterance. For a repeated utterance, a joint probability analysis is performed on (at least some of) the corresponding word sequences as recognized by one or more recognizers) and associated acoustic data. For example, a generative probabilistic model, or a maximum entropy model may be used in the analysis. The second utterance may be a repetition of the first utterance using the exact words, or another structural transformation thereof relative to the first utterance, such as an extension that adds one or more words, a truncation that removes one or more words, or a whole or partial spelling of one or more words.
摘要翻译：描述了一种技术，通过该技术，部分地基于先前的话语，使用结构化重复模型来确定用户说出的单词和/或相应的数据库条目。对于重复的话语，对由一个或多个识别器识别的相应字序列（和至少一些）和相关联的声学数据进行联合概率分析。例如，可以在分析中使用生成概率模型或最大熵模型。第二个发音可以是使用精确的单词或相对于第一个发音的其他结构变换的第一个发音的重复，例如添加一个或多个单词的扩展，删除一个或多个单词的截断或整个或一个或多个单词的部分拼写。

2. 发明授权

US08965765B2 Structured models of repetition for speech recognition 有权
标题翻译：用于语音识别的重复结构化模型
公开(公告)号：US08965765B2
公开(公告)日：2015-02-24
申请号：US12233826
申请日：2008-09-19
申请人： Geoffrey G. Zweig , Xiao Li , Dan Bohus , Alejandro Acero , Eric J. Horvitz
发明人： Geoffrey G. Zweig , Xiao Li , Dan Bohus , Alejandro Acero , Eric J. Horvitz
IPC分类号： G10L15/00 , G10L15/18
CPC分类号： G10L15/1822
摘要： Described is a technology by which a structured model of repetition is used to determine the words spoken by a user, and/or a corresponding database entry, based in part on a prior utterance. For a repeated utterance, a joint probability analysis is performed on (at least some of) the corresponding word sequences as recognized by one or more recognizers) and associated acoustic data. For example, a generative probabilistic model, or a maximum entropy model may be used in the analysis. The second utterance may be a repetition of the first utterance using the exact words, or another structural transformation thereof relative to the first utterance, such as an extension that adds one or more words, a truncation that removes one or more words, or a whole or partial spelling of one or more words.
摘要翻译：描述了一种技术，通过该技术，部分地基于先前的话语，使用结构化重复模型来确定用户说出的单词和/或相应的数据库条目。对于重复的话语，对由一个或多个识别器识别的相应字序列（和至少一些）和相关联的声学数据进行联合概率分析。例如，可以在分析中使用生成概率模型或最大熵模型。第二个发音可以是使用精确的单词或相对于第一个发音的其他结构变换的第一个发音的重复，例如添加一个或多个单词的扩展，删除一个或多个单词的截断或整个或一个或多个单词的部分拼写。

3. 发明申请

US20080281806A1 SEARCHING A DATABASE OF LISTINGS 有权
标题翻译：搜索列表数据库
公开(公告)号：US20080281806A1
公开(公告)日：2008-11-13
申请号：US11746847
申请日：2007-05-10
申请人： Ye-Yi Wang , Dong Yu , Yun-Cheng Ju , Alejandro Acero , Geoffrey G. Zweig
发明人： Ye-Yi Wang , Dong Yu , Yun-Cheng Ju , Alejandro Acero , Geoffrey G. Zweig
IPC分类号： G06F17/30
CPC分类号： G06F17/30663 , G06F3/0641 , G06F17/3069 , G10L15/187 , G10L15/197
摘要： A database having listings rather than long documents is searched using a term frequency-inverse document frequency (Tf/Idf) algorithm.
摘要翻译：使用术语频率 - 逆文档频率（Tf / Idf）算法搜索具有列表而不是长文档的数据库。

4. 发明授权

US09218412B2 Searching a database of listings 有权
标题翻译：搜索列表的数据库
公开(公告)号：US09218412B2
公开(公告)日：2015-12-22
申请号：US11746847
申请日：2007-05-10
申请人： Ye-Yi Wang , Dong Yu , Yun-Cheng Ju , Alejandro Acero , Geoffrey G. Zweig
发明人： Ye-Yi Wang , Dong Yu , Yun-Cheng Ju , Alejandro Acero , Geoffrey G. Zweig
IPC分类号： G06F7/00 , G06F17/30 , G06F3/06 , G10L15/187 , G10L15/197
CPC分类号： G06F17/30663 , G06F3/0641 , G06F17/3069 , G10L15/187 , G10L15/197
摘要： A database having listings rather than long documents is searched using a term frequency-inverse document frequency (Tf/Idf) algorithm.
摘要翻译：使用术语频率 - 逆文档频率（Tf / Idf）算法搜索具有列表而不是长文档的数据库。

5. 发明申请

US20110224982A1 AUTOMATIC SPEECH RECOGNITION BASED UPON INFORMATION RETRIEVAL METHODS 审中-公开
标题翻译：基于信息检索方法的自动语音识别
公开(公告)号：US20110224982A1
公开(公告)日：2011-09-15
申请号：US12722556
申请日：2010-03-12
申请人： Alejandro Acero , James Garnet Droppo, III , Xiaoqiang Xiao , Geoffrey G. Zweig
发明人： Alejandro Acero , James Garnet Droppo, III , Xiaoqiang Xiao , Geoffrey G. Zweig
IPC分类号： G10L15/02
CPC分类号： G10L15/08 , G10L2015/025
摘要： Described is a technology in which information retrieval (IR) techniques are used in a speech recognition (ASR) system. Acoustic units (e.g., phones, syllables, multi-phone units, words and/or phrases) are decoded, and features found from those acoustic units. The features are then used with IR techniques (e.g., TF-IDF based retrieval) to obtain a target output (a word or words). Also described is the use of IR techniques to provide a full large vocabulary continuous speech (LVCSR) recognizer
摘要翻译：描述了在语音识别（ASR）系统中使用信息检索（IR）技术的技术。声学单元（例如，电话，音节，多电话单元，单词和/或短语）被解码，并且从那些声学单元找到的特征。然后将特征与IR技术（例如，基于TF-IDF的检索）一起使用以获得目标输出（一个或多个单词）。还描述了使用IR技术来提供完整的大词汇连续语音（LVCSR）识别器

6. 发明申请

US20120158703A1 SEARCH LEXICON EXPANSION 有权
标题翻译：搜索LEXICON EXPANSION
公开(公告)号：US20120158703A1
公开(公告)日：2012-06-21
申请号：US12970477
申请日：2010-12-16
申请人： Xiao Li , Jingjing Liu , Alejandro Acero , Ye-Yi Wang
发明人： Xiao Li , Jingjing Liu , Alejandro Acero , Ye-Yi Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30737 , G06F17/2735 , G06F17/30693 , G06F17/30864
摘要： One or more techniques and/or systems are disclosed for creating an expanded or improved lexicon for use in search-based semantic tagging. A set of first documents can be identified using a set of first lexicon elements as queries, and one or more first document patterns can be extracted from the set of first documents. The document patterns can be used to find one or more second documents in a query log that comprise the document patterns, which are associated with query terms used to return the second documents. The query terms for the second documents can be extracted and used to expand the lexicon. Elements within the lexicon may be weighted based upon relevance to different query domains, for example.
摘要翻译：公开了一种或多种技术和/或系统，用于创建用于基于搜索的语义标签中的扩展或改进的词典。可以使用一组第一词典元素作为查询来识别一组第一文档，并且可以从该组第一文档中提取一个或多个第一文档图案。文档模式可用于在查询日志中找到构成文档模式的一个或多个第二文档，这些文档模式与用于返回第二个文档的查询术语相关联。可以提取和使用第二个文档的查询条款来扩展词典。例如，词法中的元素可以基于与不同查询域的相关性来加权。

7. 发明申请

US20110251844A1 GRAPHEME-TO-PHONEME CONVERSION USING ACOUSTIC DATA 有权
标题翻译：使用声学数据的图形到电声转换
公开(公告)号：US20110251844A1
公开(公告)日：2011-10-13
申请号：US13164683
申请日：2011-06-20
申请人： Xiao Li , Asela J. R. Gunawardana , Alejandro Acero
发明人： Xiao Li , Asela J. R. Gunawardana , Alejandro Acero
IPC分类号： G10L15/04
CPC分类号： G10L13/08 , G10L15/063 , G10L15/187
摘要： Described is the use of acoustic data to improve grapheme-to-phoneme conversion for speech recognition, such as to more accurately recognize spoken names in a voice-dialing system. A joint model of acoustics and graphonemes (acoustic data, phonemes sequences, grapheme sequences and an alignment between phoneme sequences and grapheme sequences) is described, as is retraining by maximum likelihood training and discriminative training in adapting graphoneme model parameters using acoustic data. Also described is the unsupervised collection of grapheme labels for received acoustic data, thereby automatically obtaining a substantial number of actual samples that may be used in retraining. Speech input that does not meet a confidence threshold may be filtered out so as to not be used by the retrained model.
摘要翻译：描述了使用声学数据来改进用于语音识别的字形到音素转换，例如更准确地识别语音拨号系统中的语音名称。描述了声学和图形（声学数据，音素序列，字形序列以及音素序列和图形序列之间的对齐）的联合模型，正如通过使用声学数据适应图形模型参数的最大似然训练和鉴别训练来重新训练。还描述了用于接收的声学数据的无监督的字母标签集合，从而自动获得可用于再培训的大量实际样本。不满足置信阈值的语音输入可以被滤除，以便不被再培训的模型使用。

8. 发明申请

US20060129397A1 System and method for identifying semantic intent from acoustic information 有权
公开(公告)号：US20060129397A1
公开(公告)日：2006-06-15
申请号：US11009630
申请日：2004-12-10
申请人： Xiao Li , Asela Gunawardana , Alejandro Acero , Milind Mahajan , Dong Yu
发明人： Xiao Li , Asela Gunawardana , Alejandro Acero , Milind Mahajan , Dong Yu
IPC分类号： G10L15/06
CPC分类号： G10L15/19 , G10L15/1815
摘要： In accordance with one embodiment of the present invention, unanticipated semantic intents are discovered in audio data in an unsupervised manner. For instance, the audio acoustics are clustered based on semantic intent and representative acoustics are chosen for each cluster. The human then need only listen to a small number of representative acoustics for each cluster (and possibly only one per cluster) in order to identify the unforeseen semantic intents.

9. 发明授权

US09928296B2 Search lexicon expansion 有权
公开(公告)号：US09928296B2
公开(公告)日：2018-03-27
申请号：US12970477
申请日：2010-12-16
申请人： Xiao Li , Jingjing Liu , Alejandro Acero , Ye-Yi Wang
发明人： Xiao Li , Jingjing Liu , Alejandro Acero , Ye-Yi Wang
IPC分类号： G06F17/30 , G06F17/27
CPC分类号： G06F17/30737 , G06F17/2735 , G06F17/30693 , G06F17/30864
摘要： One or more techniques and/or systems are disclosed for creating an expanded or improved lexicon for use in search-based semantic tagging. A set of first documents can be identified using a set of first lexicon elements as queries, and one or more first document patterns can be extracted from the set of first documents. The document patterns can be used to find one or more second documents in a query log that comprise the document patterns, which are associated with query terms used to return the second documents. The query terms for the second documents can be extracted and used to expand the lexicon. Elements within the lexicon may be weighted based upon relevance to different query domains, for example.

10. 发明授权

US07634406B2 System and method for identifying semantic intent from acoustic information 有权
标题翻译：用于从声学信息中识别语义意图的系统和方法
公开(公告)号：US07634406B2
公开(公告)日：2009-12-15
申请号：US11009630
申请日：2004-12-10
申请人： Xiao Li , Asela J. Gunawardana , Alejandro Acero , Milind Mahajan , Dong Yu
发明人： Xiao Li , Asela J. Gunawardana , Alejandro Acero , Milind Mahajan , Dong Yu
IPC分类号： G10L15/06
CPC分类号： G10L15/19 , G10L15/1815
摘要： In accordance with one embodiment of the present invention, unanticipated semantic intents are discovered in audio data in an unsupervised manner. For instance, the audio acoustics are clustered based on semantic intent and representative acoustics are chosen for each cluster. The human then need only listen to a small number of representative acoustics for each cluster (and possibly only one per cluster) in order to identify the unforeseen semantic intents.
摘要翻译：根据本发明的一个实施例，以无监督的方式在音频数据中发现意外的语义意图。例如，音频声学基于语义意图进行聚类，并为每个群集选择代表性的声学。然后，人们只需要听每个群集的少量代表性声学（并且可能只有一个群集），以便识别不可预见的语义意图。

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