Method and system for building a domain specific statistical language model from rule based grammar specifications
    2.
    发明授权
    Method and system for building a domain specific statistical language model from rule based grammar specifications 有权
    从基于规则的语法规范构建域特定统计语言模型的方法和系统

    公开(公告)号:US07346495B1

    公开(公告)日:2008-03-18

    申请号:US10130859

    申请日:2000-09-30

    IPC分类号: G06F17/21 G06F17/27 G10L15/00

    摘要: A method and system providing a statistical representation from rule-based grammar specifications. The language model is generated by obtaining a statistical representation of a rule-based language model and combining it with a statistical representation of a statistical language model for use as a final language model. The language model may be enhanced by applying smoothing and/or adapting for use as the final language model.

    摘要翻译: 一种从基于规则的语法规范提供统计表示的方法和系统。 语言模型是通过获得基于规则的语言模型的统计表示并将其与用作最终语言模型的统计语言模型的统计表示相结合而产生的。 可以通过应用平滑和/或适应来作为最终语言模型来增强语言模型。

    Method and system for using rule-based knowledge to build a class-based domain specific statistical language model
    3.
    发明授权
    Method and system for using rule-based knowledge to build a class-based domain specific statistical language model 失效
    使用基于规则的知识构建基于类的域特定统计语言模型的方法和系统

    公开(公告)号:US07275033B1

    公开(公告)日:2007-09-25

    申请号:US10130860

    申请日:2000-09-30

    IPC分类号: G10L15/18 G06F17/27

    CPC分类号: G10L15/197 G10L15/183

    摘要: A method and system for providing a class-based statistical language model representation from rule-based knowledge is disclosed. The class-based language model is generated from a statistical representation of a class-based rule net. A class-based rule net is generated using the domain-related rules with words replaced with their corresponding class-tags that are manually defined. The class-based statistical representation from the class-based rule net is combined with a class-based statistical representation from a statistical language model to generate a language model. The language model is enhanced by smoothing/adapting with general-purpose and/or domain-related corpus for use as the final language model. A two-pass search algorithm is applied for speech decoding.

    摘要翻译: 公开了一种基于规则的知识提供基于类的统计语言模型表示的方法和系统。 基于类的语言模型是从基于类的规则网的统计表示生成的。 使用与域相关的规则生成基于类的规则网,其中单词替换为手动定义的相应类标签。 基于类的规则网络的基于类的统计表示与来自统计语言模型的基于类的统计表示相结合以生成语言模型。 通过使用通用和/或域相关语料库进行平滑/调整,作为最终语言模型来增强语言模型。 双路搜索算法应用于语音解码。

    Coupled hidden Markov model (CHMM) for continuous audiovisual speech recognition
    4.
    发明授权
    Coupled hidden Markov model (CHMM) for continuous audiovisual speech recognition 有权
    耦合隐马尔可夫模型(CHMM)用于连续视听语音识别

    公开(公告)号:US07454342B2

    公开(公告)日:2008-11-18

    申请号:US10392709

    申请日:2003-03-19

    IPC分类号: G10L15/14

    摘要: Method and apparatus for an audiovisual continuous speech recognition (AVCSR) system using a coupled hidden Markov model (CHMM) are described herein. In one aspect, an exemplary process includes receiving an audio data stream and a video data stream, and performing continuous speech recognition based on the audio and video data streams using a plurality of hidden Markov models (HMMs), a node of each of the HMMs at a time slot being subject to one or more nodes of related HMMs at a preceding time slot. Other methods and apparatuses are also described.

    摘要翻译: 本文描述了使用耦合隐马尔可夫模型(CHMM)的视听连续语音识别(AVCSR)系统的方法和装置。 在一个方面,示例性过程包括接收音频数据流和视频数据流,以及使用多个隐马尔可夫模型(HMM),基于音频和视频数据流执行连续语音识别,每个HMM的节点 在时隙处于前一时隙处的相关HMM的一个或多个节点。 还描述了其它方法和装置。