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公开(公告)号：US08612232B2
公开(公告)日：2013-12-17
申请号：US13775546
申请日：2013-02-25
Applicant: AT&T Intellectual Property II, L.P.
Inventor： Srinivas Bangalore , Narendra K. Gupta , Mazin G. Rahim
CPC classification number: G10L15/1815 , G06F17/2785 , G10L13/043 , G10L15/02 , G10L15/1822 , G10L15/265
Abstract: A system and method are disclosed that improve automatic speech recognition in a spoken dialog system. The method comprises partitioning speech recognizer output into self-contained clauses, identifying a dialog act in each of the self-contained clauses, qualifying dialog acts by identifying a current domain object and/or a current domain action, and determining whether further qualification is possible for the current domain object and/or current domain action. If further qualification is possible, then the method comprises identifying another domain action and/or another domain object associated with the current domain object and/or current domain action, reassigning the another domain action and/or another domain object as the current domain action and/or current domain object and then recursively qualifying the new current domain action and/or current object. This process continues until nothing is left to qualify.
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Patent Agency Ranking
公开(公告)号：US20130246069A1
公开(公告)日：2013-09-19
申请号：US13891447
申请日：2013-05-10
Applicant: AT&T INTELLECTUAL PROPERTY II, L.P.
Inventor： Srinivas Bangalore , Junlan Feng , Mazin G. Rahim
IPC: G10L15/22
CPC classification number: G10L13/08 , G06F17/27 , G10L15/063 , G10L15/183 , G10L15/22 , H04M3/4936
Abstract: Disclosed is a method for training a spoken dialog service component from website data. Spoken dialog service components typically include an automatic speech recognition module, a language understanding module, a dialog management module, a language generation module and a text-to-speech module. The method includes selecting anchor texts within a website based on a term density, weighting those anchor texts based on a percent of salient words to total words, and incorporating the weighted anchor texts into a live spoken dialog interface, the weights determining a level of incorporation into the live spoken dialog interface.
Abstract translation: 公开了一种从网站数据训练口语对话服务组件的方法。 口语对话服务组件通常包括自动语音识别模块，语言理解模块，对话管理模块，语言生成模块和文本到语音模块。 该方法包括基于术语密度选择网站内的锚文本，基于显着词的百分比将总计文本加权到总词，并将加权的锚文本加入到现场语音对话界面中，权重确定并入级别 进入现场对话界面。
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23.发明授权公开(公告)号：US09548051B2
公开(公告)日：2017-01-17
申请号：US15014070
申请日：2016-02-03
Applicant: AT&T Intellectual Property II, L.P.
Inventor： Srinivas Bangalore , Narendra K. Gupta , Mazin G. Rahim
CPC classification number: G10L15/1815 , G06F17/2785 , G10L13/043 , G10L15/02 , G10L15/1822 , G10L15/265
Abstract: A system and method are disclosed that improve automatic speech recognition in a spoken dialog system. The method comprises partitioning speech recognizer output into self-contained clauses, identifying a dialog act in each of the self-contained clauses, qualifying dialog acts by identifying a current domain object and/or a current domain action, and determining whether further qualification is possible for the current domain object and/or current domain action. If further qualification is possible, then the method comprises identifying another domain action and/or another domain object associated with the current domain object and/or current domain action, reassigning the another domain action and/or another domain object as the current domain action and/or current domain object and then recursively qualifying the new current domain action and/or current object. This process continues until nothing is left to qualify.
Abstract translation: 公开了一种提高口语对话系统中的自动语音识别的系统和方法。 该方法包括将语音识别器输出划分为独立子句，识别每个自包含子句中的对话行为，通过识别当前域对象和/或当前域动作进行限定对话行为，以及确定是否可进行进一步的限定 对于当前域对象和/或当前域操作。 如果可以进一步鉴定，则该方法包括识别与当前域对象和/或当前域操作相关联的另一域操作和/或另一域对象，将另一域操作和/或另一域对象重新分配为当前域动作，以及 /或当前域对象，然后递归地限定新的当前域操作和/或当前对象。 这个过程一直持续到没有什么是剩下的资格。
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24.发明授权公开(公告)号：US09176946B2
公开(公告)日：2015-11-03
申请号：US14499888
申请日：2014-09-29
Applicant: AT&T Intellectual Property II, L.P.
Inventor： Srinivas Bangalore , Narendra K. Gupta , Mazin G. Rahim
CPC classification number: G06F17/2705 , G06F17/218 , G06F17/27 , G06F17/2775 , G10L15/05 , G10L15/26 , G10L2015/025 , G10L2015/081 , G10L2015/088
Abstract: A clausifier and method of extracting clauses for spoken language understanding are disclosed. The method relates to generating a set of clauses from speech utterance text and comprises inserting at least one boundary tag in speech utterance text related to sentence boundaries, inserting at least one edit tag indicating a portion of the speech utterance text to remove, and inserting at least one conjunction tag within the speech utterance text. The result is a set of clauses that may be identified within the speech utterance text according to the inserted at least one boundary tag, at least one edit tag and at least one conjunction tag. The disclosed clausifier comprises a sentence boundary classifier, an edit detector classifier, and a conjunction detector classifier. The clausifier may comprise a single classifier or a plurality of classifiers to perform the steps of identifying sentence boundaries, editing text, and identifying conjunctions within the text.
Abstract translation: 公开了一种提取语言理解条款的分类器和方法。 该方法涉及从语音话语文本生成一组子句，并且包括在与句子边界相关的语音话语文本中插入至少一个边界标签，插入指示语音话语文本的一部分的至少一个编辑标签以移除，并插入到 讲话话语文本内的至少一个连接标签。 结果是可以根据插入的至少一个边界标签，至少一个编辑标签和至少一个连接标签在语音发音文本内识别的一组子句。 所公开的分类器包括句子边界分类器，编辑检测器分类器和连接检测器分类器。 克隆器可以包括单个分类器或多个分类器，以执行识别句子边界，编辑文本以及识别文本内的连词的步骤。
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25.发明授权Unsupervised and active learning in automatic speech recognition for call classification 有权无监督和主动学习自动语音识别呼叫分类公开(公告)号：US09159318B2
公开(公告)日：2015-10-13
申请号：US14468375
申请日：2014-08-26
Applicant: AT&T Intellectual Property II, L.P.
Inventor： Dilek Z. Hakkani-Tur , Mazin G. Rahim , Giuseppe Riccardi , Gokhan Tur
CPC classification number: G10L15/063 , G10L15/07 , G10L15/18 , G10L15/26 , G10L2015/0638
Abstract: Utterance data that includes at least a small amount of manually transcribed data is provided. Automatic speech recognition is performed on ones of the utterance data not having a corresponding manual transcription to produce automatically transcribed utterances. A model is trained using all of the manually transcribed data and the automatically transcribed utterances. A predetermined number of utterances not having a corresponding manual transcription are intelligently selected and manually transcribed. Ones of the automatically transcribed data as well as ones having a corresponding manual transcription are labeled. In another aspect of the invention, audio data is mined from at least one source, and a language model is trained for call classification from the mined audio data to produce a language model.
Abstract translation: 提供了至少包含少量手动转录数据的语音数据。 对没有相应的手动转录的话语数据中的一个进行自动语音识别以产生自动转录的话语。 使用所有手动转录数据和自动转录的话语训练模型。 智能地选择并且手动地转录预定数量的不具有对应的手动转录的话语。 自动转录的数据以及具有相应手动转录的数据的标签。 在本发明的另一方面，音频数据从至少一个源开始，并且语言模型被训练用于从所开采的音频数据进行呼叫分类以产生语言模型。
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公开(公告)号：US08949127B2
公开(公告)日：2015-02-03
申请号：US14182017
申请日：2014-02-17
Applicant: AT&T Intellectual Property II, L.P.
Inventor： Mazin G. Rahim , Giuseppe Riccardi , Jeremy Huntley Wright , Bruce Melvin Buntschuh , Allen Louis Gorin
CPC classification number: G10L15/142
Abstract: A system and a method are provided. A speech recognition processor receives unconstrained input speech and outputs a string of words. The speech recognition processor is based on a numeric language that represents a subset of a vocabulary. The subset includes a set of words identified as being for interpreting and understanding number strings. A numeric understanding processor contains classes of rules for converting the string of words into a sequence of digits. The speech recognition processor utilizes an acoustic model database. A validation database stores a set of valid sequences of digits. A string validation processor outputs validity information based on a comparison of a sequence of digits output by the numeric understanding processor with valid sequences of digits in the validation database.
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