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    Unsupervised and active learning in automatic speech recognition for call classification
    1.
    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：US08818808B2

    公开(公告)日：2014-08-26

    申请号：US11063910

    申请日：2005-02-23

    申请人： Dilek Z. Hakkani-Tur ,  Mazin G. Rahim ,  Giuseppe Riccardi ,  Gokhan Tur

    发明人： Dilek Z. Hakkani-Tur ,  Mazin G. Rahim ,  Giuseppe Riccardi ,  Gokhan Tur

    IPC分类号： G10L15/06

    CPC分类号： G10L15/063 ,  G10L15/07 ,  G10L15/18 ,  G10L15/26 ,  G10L2015/0638

    摘要： 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.

    摘要翻译： 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。

    RECOGNIZING THE NUMERIC LANGUAGE IN NATURAL SPOKEN DIALOGUE
    2.
    发明申请
    RECOGNIZING THE NUMERIC LANGUAGE IN NATURAL SPOKEN DIALOGUE 有权
    识别自然语言对话中的数字语言

    公开(公告)号：US20120041763A1

    公开(公告)日：2012-02-16

    申请号：US13280884

    申请日：2011-10-25

    申请人： Mazin G. Rahim ,  Giuseppe Riccardi ,  Jeremy Huntley Wright ,  Bruce Melvin Buntschuh ,  Allen Louis Gorin

    发明人： Mazin G. Rahim ,  Giuseppe Riccardi ,  Jeremy Huntley Wright ,  Bruce Melvin Buntschuh ,  Allen Louis Gorin

    IPC分类号： G10L15/14

    CPC分类号： G10L15/142

    摘要： 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.

    摘要翻译： 提供了一种系统和方法。 语音识别处理器接收无约束输入语音并输出一串字。 语音识别处理器基于代表词汇子集的数字语言。 该子集包括被识别为用于解释和理解数字串的一组单词。 数字理解处理器包含用于将字符串转换为数字序列的规则类型。 语音识别处理器利用声学模型数据库。 验证数据库存储一组有效的数字序列。 字符串验证处理器基于数字理解处理器输出的数字序列与验证数据库中的有效数字序列的比较来输出有效性信息。

    System and method of word graph matrix decomposition
    3.
    发明授权
    System and method of word graph matrix decomposition 有权
    字图矩阵分解的系统和方法

    公开(公告)号：US07603272B1

    公开(公告)日：2009-10-13

    申请号：US11765008

    申请日：2007-06-19

    申请人： Dilek Z. Hakkani-Tur ,  Giuseppe Riccardi

    发明人： Dilek Z. Hakkani-Tur ,  Giuseppe Riccardi

    IPC分类号： G10L15/00

    CPC分类号： G10L15/083

    摘要： Disclosed is a system and method of decomposing a lattice transition matrix into a block diagonal matrix. The method is applicable to automatic speech recognition but can be used in other contexts as well, such as parsing, named entity extraction and any other methods. The method normalizes the topology of any input graph according to a canonical form.

    摘要翻译： 公开了一种将晶格转移矩阵分解为块对角矩阵的系统和方法。 该方法适用于自动语音识别，但也可以在其他上下文中使用，如解析，命名实体提取和任何其他方法。 该方法根据规范形式对任何输入图的拓扑进行归一化。

    Method of generating a labeling guide for spoken dialog services
    5.
    发明授权
    Method of generating a labeling guide for spoken dialog services 有权
    生成口语对话服务标签指南的方法

    公开(公告)号：US07366655B1

    公开(公告)日：2008-04-29

    申请号：US10405858

    申请日：2003-04-02

    申请人： Narendra K. Gupta ,  Barbara B. Hollister ,  Mazin G Rahim ,  Giuseppe Riccardi

    发明人： Narendra K. Gupta ,  Barbara B. Hollister ,  Mazin G Rahim ,  Giuseppe Riccardi

    IPC分类号： G06F17/27 ,  G06F17/21

    CPC分类号： G06F17/279 ,  G10L15/18 ,  G10L15/183

    摘要： A method is disclosed for designing a labeling guide for use by a labeler in labeling data used for training a spoken language understanding (SLU) module for an application. The method comprises a labeling guide designer selecting domain-independent actions applicable to an application, selecting domain-dependent objects according to characteristics of the application, and generating a labeling guide using the selected domain-independent actions and selected domain-dependent objects. An advantage of the labeling guide generated in this manner is that the labeling guide designer can easily port the labeling guide to a new application by selecting a set of domain-independent action and then selecting the domain-dependent objects related to the new application.

    摘要翻译： 公开了一种用于设计标签指南的方法，用于标签机用于标记用于训练用于应用的口语理解（SLU）模块的数据。 该方法包括标签指导者设计者，其选择适用于应用的独立于领域的动作，根据应用的特征来选择依赖于域的对象，以及使用所选择的与域无关的动作和选择的域相关对象来生成标签指南。 以这种方式生成的标签指南的优点是，标签指南设计者可以通过选择一组独立于领域的动作，然后选择与新应用相关的域相关对象，轻松地将标签指南移植到新应用。

    Automatic clustering of tokens from a corpus for grammar acquisition
    6.
    发明授权
    Automatic clustering of tokens from a corpus for grammar acquisition 有权
    用于语法获取的语料库的令牌的自动聚类

    公开(公告)号：US07356462B2

    公开(公告)日：2008-04-08

    申请号：US10662730

    申请日：2003-09-15

    申请人： Srinivas Bangalore ,  Giuseppe Riccardi

    发明人： Srinivas Bangalore ,  Giuseppe Riccardi

    IPC分类号： G06F17/27

    CPC分类号： G06K9/6282 ,  G06K9/6218

    摘要： A method of grammar learning from a corpus comprises, for the other non-context words, generating frequency vectors for each non-context token in a corpus based upon counted occurrences of a predetermined relationship of the non-context tokens to identified context tokens. Clusters are grown from the frequency vectors according to a lexical correlation among the non-context tokens.

    摘要翻译： 基于语料库的语法学习的方法包括对于其他非上下文单词，基于对所识别的上下文令牌的非上下文令牌的预定关系的计数出现，为语料库中的每个非上下文令牌生成频率向量。 根据非上下文令牌之间的词汇相关性，从频率向量生长群集。

    Active learning process for spoken dialog systems
    7.
    发明授权
    Active learning process for spoken dialog systems 有权
    口语对话系统的主动学习过程

    公开(公告)号：US07292976B1

    公开(公告)日：2007-11-06

    申请号：US10447888

    申请日：2003-05-29

    申请人： Dilek Z. Hakkani-Tur ,  Mazin G. Rahim ,  Giuseppe Riccardi ,  Gokhan Tur

    发明人： Dilek Z. Hakkani-Tur ,  Mazin G. Rahim ,  Giuseppe Riccardi ,  Gokhan Tur

    IPC分类号： G06F17/27 ,  G10L15/00

    CPC分类号： G06F17/2775 ,  G06F17/277 ,  G10L2015/0631

    摘要： A large amount of human labor is required to transcribe and annotate a training corpus that is needed to create and update models for automatic speech recognition (ASR) and spoken language understanding (SLU). Active learning enables a reduction in the amount of transcribed and annotated data required to train ASR and SLU models. In one aspect of the present invention, an active learning ASR process and active learning SLU process are coupled, thereby enabling further efficiencies to be gained relative to a process that maintains an isolation of data in both the ASR and SLU domains.

    摘要翻译： 需要大量的人力劳动来转录和注释创建和更新自动语音识别（ASR）和语言理解（SLU）模型所需的训练语料库。 主动学习可以减少训练ASR和SLU模型所需的转录和注释数据量。 在本发明的一个方面，耦合主动学习ASR过程和主动学习SLU过程，从而相对于维持ASR和SLU域中的数据隔离的过程而获得进一步的效率。

    System for handling frequently asked questions in a natural language dialog service
    8.
    发明授权
    System for handling frequently asked questions in a natural language dialog service 有权
    用于在自然语言对话服务中处理常见问题的系统

    公开(公告)号：US07197460B1

    公开(公告)日：2007-03-27

    申请号：US10326692

    申请日：2002-12-19

    申请人： Narendra K. Gupta ,  Mazin G Rahim ,  Giuseppe Riccardi

    发明人： Narendra K. Gupta ,  Mazin G Rahim ,  Giuseppe Riccardi

    IPC分类号： G10L11/00 ,  G10L21/00

    CPC分类号： G10L15/22 ,  G06F3/167

    摘要： A voice-enabled help desk service is disclosed. The service comprises an automatic speech recognition module for recognizing speech from a user, a spoken language understanding module for understanding the output from the automatic speech recognition module, a dialog management module for generating a response to speech from the user, a natural voices text-to-speech synthesis module for synthesizing speech to generate the response to the user, and a frequently asked questions module. The frequently asked questions module handles frequently asked questions from the user by changing voices and providing predetermined prompts to answer the frequently asked question.

    摘要翻译： 公开了支持语音的帮助台服务。 该服务包括用于识别来自用户的语音的自动语音识别模块，用于理解来自自动语音识别模块的输出的口语语言理解模块，用于生成来自用户对语音的响应的对话管理模块，自然语音文本 - 语音合成模块，用于合成语音以产生对用户的响应，以及常见问题模块。 常见问题模块通过改变语音来处理用户的常见问题，并提供预定的提示来回答常见问题。