公开(公告)号：US20060271364A1

公开(公告)日：2006-11-30

申请号：US11298765

申请日：2005-12-08

申请人： Danilo Mirkovic ,  Lawrence Cavedon ,  Matthew Purver ,  Florin Ratiu ,  Tobias Scheideck ,  Fuliang Weng ,  Qi Zhang ,  Kui Xu

发明人： Danilo Mirkovic ,  Lawrence Cavedon ,  Matthew Purver ,  Florin Ratiu ,  Tobias Scheideck ,  Fuliang Weng ,  Qi Zhang ,  Kui Xu

IPC分类号： G10L15/00

CPC分类号： G06F17/28 ,  G10L2015/228

摘要： Representation-neutral dialogue systems and methods (“RNDS”) are described that include multi-application, multi-device spoken-language dialogue systems based on the information-state update approach. The RNDS includes representation-neutral core components of a dialogue system that provide scripted domain-specific extensions to routines such as dialogue move modeling and reference resolution, easy substitution of specific semantic representations and associated routines, and clean interfaces to external components for language-understanding (i.e., speech-recognition and parsing) and language-generation, and to domain-specific knowledge sources. The RNDS also resolves multi-device dialogue by evaluating and selecting among candidate dialogue moves based on features at multiple levels. Multiple sources of information are combined, multiple speech recognition and parsing hypotheses tested, and multiple device and moves considered to choose the highest scoring hypothesis overall. Confirmation and clarification behaviour can be governed by the overall score.

摘要翻译： 描述了中立的对话系统和方法（“RNDS”），其包括基于信息状态更新方法的多应用，多设备语言对话系统。 RNDS包括对话系统的代表性中立的核心组件，其提供脚本特定的例程扩展，例如对话移动建模和参考解析，容易地替换特定的语义表示和相关联的例程，以及将外部组件的界面清理为语言理解 （即语音识别和解析）和语言生成以及针对领域的知识来源。 RNDS还通过基于多层次的特征评估和选择候选对话移动来解决多设备对话。 多个信息来源相结合，多个语音识别和解析假设被测试，多个设备和移动被认为是选择最高的得分假设。 确认和澄清行为可以由总体评分来决定。

公开(公告)号：US07904297B2

公开(公告)日：2011-03-08

申请号：US11298765

申请日：2005-12-08

申请人： Danilo Mirkovic ,  Lawrence Cavedon ,  Matthew Purver ,  Florin Ratiu ,  Tobias Scheideck ,  Fuliang Weng ,  Qi Zhang ,  Kui Xu

发明人： Danilo Mirkovic ,  Lawrence Cavedon ,  Matthew Purver ,  Florin Ratiu ,  Tobias Scheideck ,  Fuliang Weng ,  Qi Zhang ,  Kui Xu

IPC分类号： G10L15/00 ,  G10L15/08

CPC分类号： G06F17/28 ,  G10L2015/228

摘要： Representation-neutral dialogue systems and methods (“RNDS”) are described that include multi-application, multi-device spoken-language dialogue systems based on the information-state update approach. The RNDS includes representation-neutral core components of a dialogue system that provide scripted domain-specific extensions to routines such as dialogue move modeling and reference resolution, easy substitution of specific semantic representations and associated routines, and clean interfaces to external components for language-understanding (i.e., speech-recognition and parsing) and language-generation, and to domain-specific knowledge sources. The RNDS also resolves multi-device dialogue by evaluating and selecting among candidate dialogue moves based on features at multiple levels. Multiple sources of information are combined, multiple speech recognition and parsing hypotheses tested, and multiple device and moves considered to choose the highest scoring hypothesis overall. Confirmation and clarification behavior can be governed by the overall score.

摘要翻译： 描述了中立的对话系统和方法（“RNDS”），其包括基于信息状态更新方法的多应用，多设备语言对话系统。 RNDS包括对话系统的代表性中立的核心组件，其提供脚本特定的例程扩展，例如对话移动建模和参考解析，容易地替换特定的语义表示和相关联的例程，以及将外部组件的界面清理为语言理解 （即语音识别和解析）和语言生成以及针对领域的知识来源。 RNDS还通过基于多层次的特征评估和选择候选对话移动来解决多设备对话。 多个信息来源相结合，多个语音识别和解析假设被测试，多个设备和移动被认为是选择最高的得分假设。 确认和澄清行为可以由总体评分来决定。

公开(公告)号：US07925507B2

公开(公告)日：2011-04-12

申请号：US11483840

申请日：2006-07-07

申请人： Fuliang Weng ,  Tobias Scheideck ,  Zhe Feng ,  Badri Raghunathan

发明人： Fuliang Weng ,  Tobias Scheideck ,  Zhe Feng ,  Badri Raghunathan

IPC分类号： G10L15/18

CPC分类号： G06F17/278 ,  G06F17/30654 ,  G10L15/22

摘要： Embodiments of a name recognition process for use in dialog systems are described. In one embodiment, the name recognition process assigns weighting values to names used in a dialog based on the usage of these names. This process takes advantage of the general tendency of people to speak names, either full or partial, only after they have heard or read these names. Name input is taken in several different forms, including a static background database that contains all possible names, a background database that contains commonly used names (such as common trademarks or references), a database that contains names from a user model, and a dynamic database that constantly takes the names just mentioned. The names are then appended with proper weighting values. A high weight is given to names that have been mentioned recently, a lower weight is given to common names, and a lowest weight is given to names for the ones that have never been used or mentioned.

摘要翻译： 描述在对话系统中使用的名称识别过程的实施例。 在一个实施例中，名称识别过程基于这些名称的使用，将加权值分配给对话中使用的名称。 这个过程只有在听到或读过这些名字之后才能利用人们的全部或部分名字的一般倾向。 名称输入采用几种不同的形式，包括包含所有可能名称的静态后台数据库，包含常用名称（如公共商标或引用）的后台数据库，包含用户模型名称的数据库和动态 数据库不断提供刚才提到的名称。 然后，这些名称将附加适当的权重值。 给予最近提到的名称较高的重量，较低的重量被赋予通用名称，而对于从未被使用或提及的那些的名称来说，最小的重量是给予的。

公开(公告)号：US20080010058A1

公开(公告)日：2008-01-10

申请号：US11483840

申请日：2006-07-07

申请人： Fuliang Weng ,  Tobias Scheideck ,  Zhe Feng ,  Badri Raghunathan

发明人： Fuliang Weng ,  Tobias Scheideck ,  Zhe Feng ,  Badri Raghunathan

IPC分类号： G06F17/27

CPC分类号： G06F17/278 ,  G06F17/30654 ,  G10L15/22

摘要： Embodiments of a name recognition process for use in dialog systems are described. In one embodiment, the name recognition process assigns weighting values to names used in a dialog based on the usage of these names. This process takes advantage of the general tendency of people to speak names, either full or partial, only after they have heard or read these names. Name input is taken in several different forms, including a static background database that contains all possible names, a background database that contains commonly used names (such as common trademarks or references), a database that contains names from a user model, and a dynamic database that constantly takes the names just mentioned. The names are then appended with proper weighting values. A high weight is given to names that have been mentioned recently, a lower weight is given to common names, and a lowest weight is given to names for the ones that have never been used or mentioned.

摘要翻译： 描述在对话系统中使用的名称识别过程的实施例。 在一个实施例中，名称识别过程基于这些名称的使用，将加权值分配给对话中使用的名称。 这个过程只有在听到或读过这些名字之后才能利用人们的全部或部分名字的一般倾向。 名称输入采用几种不同的形式，包括包含所有可能名称的静态后台数据库，包含常用名称（如公共商标或引用）的后台数据库，包含用户模型名称的数据库和动态 数据库不断提供刚才提到的名称。 然后，这些名称将附加适当的权重值。 给予最近提到的名称较高的重量，较低的重量被赋予通用名称，而对于从未被使用或提及的那些的名称来说，最小的重量是给予的。