利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

79 条记录 (耗时 0.032 秒)

    METHOD FOR BUILDING A NATURAL LANGUAGE UNDERSTANDING MODEL FOR A SPOKEN DIALOG SYSTEM
    22.
    发明申请
    METHOD FOR BUILDING A NATURAL LANGUAGE UNDERSTANDING MODEL FOR A SPOKEN DIALOG SYSTEM 有权
    用于建立自然语言的方法来理解对讲机系统的模型

    公开(公告)号：US20100042404A1

    公开(公告)日：2010-02-18

    申请号：US12582062

    申请日：2009-10-20

    申请人： Narendra K. Gupta ,  Mazin G. Rahim ,  Gokhan Tur ,  Antony Van der Mude

    发明人： Narendra K. Gupta ,  Mazin G. Rahim ,  Gokhan Tur ,  Antony Van der Mude

    IPC分类号： G10L15/18 ,  G06F17/27

    CPC分类号： G10L15/193 ,  G10L15/063 ,  G10L15/183

    摘要： A method of generating a natural language model for use in a spoken dialog system is disclosed. The method comprises using sample utterances and creating a number of hand crafted rules for each call-type defined in a labeling guide. A first NLU model is generated and tested using the hand crafted rules and sample utterances. A second NLU model is built using the sample utterances as new training data and using the hand crafted rules. The second NLU model is tested for performance using a first batch of labeled data. A series of NLU models are built by adding a previous batch of labeled data to training data and using a new batch of labeling data as test data to generate the series of NLU models with training data that increases constantly. If not all the labeling data is received, the method comprises repeating the step of building a series of NLU models until all labeling data is received. After all the training data is received, at least once, the method comprises building a third NLU model using all the labeling data, wherein the third NLU model is used in generating the spoken dialog service.

    摘要翻译： 公开了一种生成在口头对话系统中使用的自然语言模型的方法。 该方法包括对标签指南中定义的每个呼叫类型使用样本话语和创建许多手工制作规则。 使用手工制作的规则和样品说话来生成和测试第一个NLU模型。 使用示例语句作为新的训练数据并使用手工制作规则构建了第二个NLU模型。 使用第一批标签数据对第二个NLU模型进行性能测试。 通过将前一批标签数据添加到训练数据并使用新批签名数据作为测试数据来生成一系列NLU模型，训练数据不断增加，构建了一系列NLU模型。 如果不是全部接收到标签数据，则该方法包括重复建立一系列NLU模型的步骤，直到接收到所有标记数据为止。 在接收到所有训练数据之后，至少一次，该方法包括使用所有标签数据构建第三NLU模型，其中第三NLU模型用于生成口语对话服务。

    Method and apparatus for automatically building conversational systems
    23.
    发明授权
    Method and apparatus for automatically building conversational systems 有权
    自动构建对话系统的方法和装置

    公开(公告)号：US07660400B2

    公开(公告)日：2010-02-09

    申请号：US10742466

    申请日：2003-12-19

    申请人： Srinivas Bangalore ,  Junlan Feng ,  Mazin G. Rahim

    发明人： Srinivas Bangalore ,  Junlan Feng ,  Mazin G. Rahim

    IPC分类号： H04M1/64

    CPC分类号： G06F17/243 ,  G06Q10/06311 ,  G06Q30/0201 ,  G06Q30/0635 ,  H04L12/6418 ,  H04M3/4938 ,  H04M7/0009 ,  H04M7/0036 ,  H04M2201/40 ,  H04M2201/60 ,  H04M2203/355

    摘要： A system and method provides a natural language interface to world-wide web content. Either in advance or dynamically, webpage content is parsed using a parsing algorithm. A person using a telephone interface can provide speech information, which is converted to text and used to automatically fill in input fields on a webpage form. The form is then submitted to a database search and a response is generated. Information contained on the responsive webpage is extracted and converted to speech via a text-to-speech engine and communicated to the person.

    摘要翻译： 系统和方法为世界各地的Web内容提供了一种自然语言界面。 提前或动态地，使用解析算法解析网页内容。 使用电话接口的人可以提供语音信息，其被转换成文本并用于自动填写网页表单上的输入字段。 然后将表单提交到数据库搜索，并生成响应。 包含在响应网页上的信息被提取并经由文本到语音引擎转换成语音，并传达给该人。

    System and method of providing a spoken dialog interface to a website
    24.
    发明授权
    System and method of providing a spoken dialog interface to a website 有权
    向网站提供口语对话界面的系统和方法

    公开(公告)号：US07580842B1

    公开(公告)日：2009-08-25

    申请号：US11928886

    申请日：2007-10-30

    申请人： Srinivas Bangalore ,  Junlan Feng ,  Mazin G. Rahim

    发明人： Srinivas Bangalore ,  Junlan Feng ,  Mazin G. Rahim

    IPC分类号： G10L15/22 ,  G10L13/08 ,  G10L15/18

    CPC分类号： G10L13/08 ,  G06F17/27 ,  G10L15/063 ,  G10L15/183 ,  G10L15/22 ,  H04M3/4936

    摘要： Disclosed is a system and method for generating a spoken dialog service from website data. Spoken dialog 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. These components are capable of being automatically trained from processed website data. A website analyzer converts a website into structured text data set and a structured task knowledge base. The website analyzer further extracts linguistic items from the website data. The dialog components are automatically trained from the structured text data set, structured task knowledge base and linguistic items.

    摘要翻译： 公开了一种用于从网站数据生成口语对话服务的系统和方法。 口语对话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。 这些组件能够被处理的网站数据自动训练。 网站分析器将网站转换为结构化文本数据集和结构化任务知识库。 网站分析器进一步从网站数据中提取语言项目。 对话组件由结构化文本数据集，结构化任务知识库和语言项目自动进行训练。

    Method of generating a labeling guide for spoken dialog services
    25.
    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。

    Active learning process for spoken dialog systems
    26.
    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
    27.
    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。

    Spoken language understanding that incorporates prior knowledge into boosting
    28.
    发明授权
    Spoken language understanding that incorporates prior knowledge into boosting 有权
    将先前知识纳入提升的口语理解

    公开(公告)号：US07152029B2

    公开(公告)日：2006-12-19

    申请号：US10160461

    申请日：2002-05-31

    申请人： Hiyan Alshawi ,  Giuseppe DiFabbrizio ,  Narendra K. Gupta ,  Mazin G. Rahim ,  Robert E. Schapire ,  Yoram Singer

    发明人： Hiyan Alshawi ,  Giuseppe DiFabbrizio ,  Narendra K. Gupta ,  Mazin G. Rahim ,  Robert E. Schapire ,  Yoram Singer

    IPC分类号： G06F17/20

    CPC分类号： G10L15/063

    摘要： A system for understanding entries, such as speech, develops a classifier by employing prior knowledge with which a given corpus of training entries is enlarged threefold. A rule is created for each of the labels employed in the classifyier, and the created rules are applied to the given corpus to create a corpus of attachments by appending a weight of ηp(x), or 1−ηp(x), to labels of entries that meet, or fail to meet, respectively, conditions of the labels' rules, and to also create a corpus of non-attachments by appending a weight of 1−ηp(x), or ηp(x), to labels of entries that meet, or fail to meet conditions of the labels' rules.

    摘要翻译： 用于理解诸如言语之类的条目的系统通过采用将给定的训练条目语料库放大三倍的先验知识来开发分类器。 为分类器中使用的每个标签创建一个规则，并将创建的规则应用于给定的语料库以通过将etap（x）或1-etap（x）的权重附加到标签来创建附件语料库 分别符合或未能满足标签规则的条件的条目，并通过将1-etap（x）或etap（x）的权重附加到标签的标签上来创建非附件语料库 满足或不符合标签规则条件的条目。

    Method and apparatus for speech recognition using second order statistics and linear estimation of cepstral coefficients
    29.
    发明授权
    Method and apparatus for speech recognition using second order statistics and linear estimation of cepstral coefficients 失效
    使用二阶统计学和倒谱系数的线性估计的语音识别方法和装置

    公开(公告)号：US06202047B1

    公开(公告)日：2001-03-13

    申请号：US09050301

    申请日：1998-03-30

    申请人： Yariv Ephraim ,  Mazin G. Rahim

    发明人： Yariv Ephraim ,  Mazin G. Rahim

    IPC分类号： G10L1514

    CPC分类号： G10L15/02 ,  G10L15/142 ,  G10L25/24

    摘要： A method and apparatus for speech recognition using second order statistics and linear estimation of cepstral coefficients. In one embodiment, a speech input signal is received and cepstral features are extracted. An answer is generated using the extracted cepstral features and a fixed signal independent diagonal matrix as the covariance matrix for the cepstral components of the speech input signal and, for example, a hidden Markov model. In another embodiment, a noisy speech input signal is received and a cepstral vector representing a clean speech input signal is generated based on the noisy speech input signal and an explicit linear minimum mean square error cepstral estimator.

    摘要翻译： 一种使用二阶统计学和倒谱系数线性​​估计的语音识别的方法和装置。 在一个实施例中，接收语音输入信号并提取倒谱特征。 使用提取的倒谱特征和固定信号独立对角矩阵作为用于语音输入信号的倒谱分量的协方差矩阵和例如隐马尔可夫模型来生成答案。 在另一个实施例中，接收噪声语音输入信号，并且基于噪声语音输入信号和显式线性最小均方误差倒谱估计器产生表示干净语音输入信号的倒谱矢量。