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    Method of generation a labeling guide for spoken dialog services
    23.
    发明授权
    Method of generation 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：US07729902B1

    公开(公告)日：2010-06-01

    申请号：US11927738

    申请日：2007-10-30

    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。

    SYSTEM FOR HANDLING FREQUENTLY ASKED QUESTIONS IN A NATURAL LANGUAGE DIALOG SERVICE
    24.
    发明申请
    SYSTEM FOR HANDLING FREQUENTLY ASKED QUESTIONS IN A NATURAL LANGUAGE DIALOG SERVICE 审中-公开
    在自然语言对话服务中处理常见问题的系统

    公开(公告)号：US20090070113A1

    公开(公告)日：2009-03-12

    申请号：US12266835

    申请日：2008-11-07

    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： G10L15/18

    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。

    Method and apparatus for discriminative utterance verification using multiple confidence measures
    25.
    发明授权
    Method and apparatus for discriminative utterance verification using multiple confidence measures 失效
    使用多重置信度测度的辨别性话语验证的方法和装置

    公开(公告)号：US6125345A

    公开(公告)日：2000-09-26

    申请号：US934056

    申请日：1997-09-19

    申请人： Piyush C. Modi ,  Mazin G. Rahim

    发明人： Piyush C. Modi ,  Mazin G. Rahim

    IPC分类号： G10L15/10 ,  G10L5/06 ,  G10L9/00

    CPC分类号： G10L15/10

    摘要： A multiple confidence measures subsystem of an automated speech recognition system allows otherwise independent confidence measures to be integrated and used for both training and testing on a consistent basis. Speech to be recognized is input to a speech recognizer and a recognition verifier of the multiple confidence measures subsystem. The speech recognizer generates one or more confidence measures. The speech recognizer preferably generates a misclassification error (MCE) distance as one of the confidence measures. The recognized speech output by the speech recognizer is input to the recognition verifier, which outputs one or more confidence measures. The recognition verifier preferably outputs a misverification error (MVE) distance as one of the confidence measures. The confidence measures output by the speech recognizer and the recognition verifier are normalized and then input to an integrator. The integrator integrates the various confidence measures during both a training phase for the hidden Markov models implemented in the speech recognizer and the recognition verifier and during testing of the input speech. The integrator is preferably implemented using a multi-layer perceptron (MLP). The output of the integrator, rather than the recognition verifier, determines whether the recognized utterance hypothesis generated by the speech recognizer should be accepted or rejected.

    摘要翻译： 自动化语音识别系统的多重置信度子系统允许另外独立的置信度度量被一体化地整合并用于训练和测试。 要识别的语音被输入到多个置信度度子系统的语音识别器和识别验证器。 语音识别器生成一个或多个置信度量。 语音识别器优选地产生误分类误差（MCE）距离作为置信度测量之一。 由语音识别器输出的识别语音输入到识别验证器，该校验器输出一个或多个置信度量。 识别验证器优选地输出误差误差（MVE）距离作为置信度测量之一。 由语音识别器和识别验证器输出的置信度被归一化，然后输入到积分器。 在语音识别器和识别验证器中实现的隐马尔科夫模型的训练阶段和输入语音测试期间，积分器集成了各种置信度度量。 积分器优选地使用多层感知器（MLP）来实现。 积分器的输出而不是识别验证器确定是否应该接受或拒绝由语音识别器生成的识别的话语假设。

    System and method of recognizing an acoustic environment to adapt a set of based recognition models to the current acoustic environment for subsequent speech recognition
    26.
    发明授权
    System and method of recognizing an acoustic environment to adapt a set of based recognition models to the current acoustic environment for subsequent speech recognition 失效
    识别声学环境以使一组基于识别模型适应于当前声学环境以用于随后的语音识别的系统和方法

    公开(公告)号：US5960397A

    公开(公告)日：1999-09-28

    申请号：US863927

    申请日：1997-05-27

    申请人： Mazin G. Rahim

    发明人： Mazin G. Rahim

    IPC分类号： G10L15/14 ,  G10L15/20 ,  G10L15/26 ,  G10L5/06

    CPC分类号： G10L15/20 ,  G10L15/144 ,  G10L21/0216

    摘要： A speech recognition system which effectively recognizes unknown speech from multiple acoustic environments includes a set of secondary models, each associated with one or more particular acoustic environments, integrated with a base set of recognition models. The speech recognition system is trained by making a set of secondary models in a first stage of training, and integrating the set of secondary models with a base set of recognition models in a second stage of training.

    摘要翻译： 有效地识别来自多个声学环境的未知语音的语音识别系统包括与一组或多个识别模型集成的一组次要模型，每个次要模型与一个或多个特定声学环境相关联。 语音识别系统通过在第一阶段的训练中形成一组次级模型进行训练，并将第二级模型集合与第二阶段训练中的识别模型的基本集合进行训练。

    Speech and speaker recognition using factor analysis to model covariance structure of mixture components
    27.
    发明授权
    Speech and speaker recognition using factor analysis to model covariance structure of mixture components 失效
    使用因子分析的语音和说话人识别来模拟混合组分的协方差结构

    公开(公告)号：US5946656A

    公开(公告)日：1999-08-31

    申请号：US971838

    申请日：1997-11-17

    申请人： Mazin G. Rahim ,  Lawrence K. Saul

    发明人： Mazin G. Rahim ,  Lawrence K. Saul

    IPC分类号： G01L9/16

    CPC分类号： G10L15/144 ,  G10L17/16 ,  G10L2015/085

    摘要： Hidden Markov models (HMMs) rely on high-dimensional feature vectors to summarize the short-time properties of speech correlations between features that can arise when the speech signal is non-stationary or corrupted by noise. These correlations are modeled using factor analysis, a statistical method for dimensionality reduction. Factor analysis is used to model acoustic correlation in automatic speech recognition by introducing a small number of parameters to model the covariance structure of a speech signal. The parameters are estimated by an Expectation Maximization (EM) technique that can be embedded in the training procedures for the HMMs, and then further adjusted using Minimum Classification Error (MCE) training, which demonstrates better discrimination and produces more accurate recognition models.

    摘要翻译： 隐马尔可夫模型（HMM）依靠高维特征向量来总结当语音信号不稳定或被噪声破坏时可能出现的特征之间的语音相关性的短时性质。 这些相关性使用因子分析进行建模，这是用于降维的统计方法。 因子分析用于通过引入少量参数来建模语音信号的协方差结构来建模自动语音识别中的声学相关性。 参数通过预期最大化（EM）技术估计，可以嵌入到HMM的训练程序中，然后使用最小分类误差（MCE）训练进一步调整，这表明更好的辨别和产生更准确的识别模型。

    System and method of providing an automated data-collection in spoken dialog systems
    29.
    发明授权
    System and method of providing an automated data-collection in spoken dialog systems 有权
    在口头对话系统中提供自动数据收集的系统和方法

    公开(公告)号：US08185399B2

    公开(公告)日：2012-05-22

    申请号：US11029798

    申请日：2005-01-05

    申请人： Giuseppe Di Fabbrizio ,  Dilek Z. Hakkani-Tur ,  Mazin G. Rahim ,  Bernard S. Renger ,  Gokhan Tur

    发明人： Giuseppe Di Fabbrizio ,  Dilek Z. Hakkani-Tur ,  Mazin G. Rahim ,  Bernard S. Renger ,  Gokhan Tur

    IPC分类号： G10L21/00 ,  G10L19/00 ,  G06F17/27

    CPC分类号： G10L15/063 ,  G10L15/183 ,  G10L15/22

    摘要： The invention relates to a system and method for gathering data for use in a spoken dialog system. An aspect of the invention is generally referred to as an automated hidden human that performs data collection automatically at the beginning of a conversation with a user in a spoken dialog system. The method comprises presenting an initial prompt to a user, recognizing a received user utterance using an automatic speech recognition engine and classifying the recognized user utterance using a spoken language understanding module. If the recognized user utterance is not understood or classifiable to a predetermined acceptance threshold, then the method re-prompts the user. If the recognized user utterance is not classifiable to a predetermined rejection threshold, then the method transfers the user to a human as this may imply a task-specific utterance. The received and classified user utterance is then used for training the spoken dialog system.

    摘要翻译： 本发明涉及一种用于收集在口头对话系统中使用的数据的系统和方法。 本发明的一个方面通常被称为在与对话系统中的用户的对话开始时自动执行数据收集的自动隐藏人。 该方法包括向用户呈现初始提示，使用自动语音识别引擎识别接收到的用户话语，并使用口语理解模块对所识别的用户话语进行分类。 如果识别的用户话语不能被理解或可被分类到预定的接受阈值，则该方法重新提示用户。 如果识别的用户话语不能被分类为预定的拒绝阈值，则该方法将用户转移给人，因为这可能意味着任务特定的话语。 然后，接收和分类的用户话语用于训练口语对话系统。

    Active labeling for spoken language understanding
    30.
    发明授权
    Active labeling for spoken language understanding 有权
    积极标注口语理解

    公开(公告)号：US07949525B2

    公开(公告)日：2011-05-24

    申请号：US12485103

    申请日：2009-06-16

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

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

    IPC分类号： G10L15/00 ,  G10L15/06 ,  G10L15/20

    CPC分类号： G10L15/1822

    摘要： A spoken language understanding method and system are provided. The method includes classifying a set of labeled candidate utterances based on a previously trained classifier, generating classification types for each candidate utterance, receiving confidence scores for the classification types from the trained classifier, sorting the classified utterances based on an analysis of the confidence score of each candidate utterance compared to a respective label of the candidate utterance, and rechecking candidate utterances according to the analysis. The system includes modules configured to control a processor in the system to perform the steps of the method.

    摘要翻译： 提供口语理解方法和系统。 该方法包括基于先前训练的分类器对一组标记的候选话语进行分类，为每个候选语音生成分类类型，从训练分类器接收分类类型的置信度分数， 每个候选话语与候选话语的相应标签相比较，并且根据分析重新检查候选话语。 该系统包括被配置为控制系统中的处理器以执行该方法的步骤的模块。