公开(公告)号：US09373323B2

公开(公告)日：2016-06-21

申请号：US14617172

申请日：2015-02-09

申请人： AT&T Intellectual Property I, L.P.

发明人： Jason D. Williams

IPC分类号： G10L15/06 ,  G06F17/28

CPC分类号： G10L15/063 ,  G06F17/2881

摘要： Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for generating a natural language spoken dialog system. The method includes nominating a set of allowed dialog actions and a set of contextual features at each turn in a dialog, and selecting an optimal action from the set of nominated allowed dialog actions using a machine learning algorithm. The method includes generating a response based on the selected optimal action at each turn in the dialog. The set of manually nominated allowed dialog actions can incorporate a set of business rules. Prompt wordings in the generated natural language spoken dialog system can be tailored to a current context while following the set of business rules. A compression label can represent at least one of the manually nominated allowed dialog actions.

公开(公告)号：US20160293158A1

公开(公告)日：2016-10-06

申请号：US15185304

申请日：2016-06-17

申请人： AT&T Intellectual Property I, L.P.

发明人： Jason D. Williams

IPC分类号： G10L15/06 ,  G06F17/28

CPC分类号： G10L15/063 ,  G06F17/2881

摘要： Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for generating a natural language spoken dialog system. The method includes nominating a set of allowed dialog actions and a set of contextual features at each turn in a dialog, and selecting an optimal action from the set of nominated allowed dialog actions using a machine learning algorithm. The method includes generating a response based on the selected optimal action at each turn in the dialog. The set of manually nominated allowed dialog actions can incorporate a set of business rules. Prompt wordings in the generated natural language spoken dialog system can be tailored to a current context while following the set of business rules. A compression label can represent at least one of the manually nominated allowed dialog actions.

摘要翻译： 本文公开了用于生成自然语言对话系统的系统，计算机实现的方法和有形的计算机可读存储介质。 该方法包括在对话中的每个转弯处提取一组允许的对话动作和一组上下文特征，以及使用机器学习算法从该组指定的允许对话动作中选择最佳动作。 该方法包括在对话中的每一回合基础上产生基于所选择的最佳动作的响应。 一组手动提名的允许的对话框操作可以包含一组业务规则。 生成的自然语言对话系统中的提示字词可以根据当前上下文进行定制，同时遵循一组业务规则。 压缩标签可以表示手动指定的允许对话动作中的至少一个。

公开(公告)号：US09378738B2

公开(公告)日：2016-06-28

申请号：US14565516

申请日：2014-12-10

申请人： AT&T Intellectual Property I, L.P.

发明人： Jason D. Williams ,  Ethan Selfridge

IPC分类号： G10L15/05 ,  G10L15/22 ,  G10L15/04 ,  G10L15/06 ,  G10L15/08

CPC分类号： G10L15/222 ,  G10L15/04 ,  G10L15/05 ,  G10L15/063 ,  G10L15/083

摘要： Disclosed herein are systems, methods, and non-transitory computer-readable storage media for advanced turn-taking in an interactive spoken dialog system. A system configured according to this disclosure can incrementally process speech prior to completion of the speech utterance, and can communicate partial speech recognition results upon finding particular conditions. A first condition which, if found, allows the system to communicate partial speech recognition results, is that the most recent word found in the partial results is statistically likely to be the termination of the utterance, also known as a terminal node. A second condition is the determination that all search paths within a speech lattice converge to a common node, also known as a pinch node, before branching out again. Upon finding either condition, the system can communicate the partial speech recognition results. Stability and correctness probabilities can also determine which partial results are communicated.

摘要翻译： 这里公开了用于交互式口语对话系统中的高级转弯的系统，方法和非暂时的计算机可读存储介质。 根据本公开配置的系统可以在完成语音话语之前递增地处理语音，并且可以在发现特定条件时传送部分语音识别结果。 如果发现，允许系统传达部分语音识别结果的第一个条件是，在部分结果中发现的最新字词在统计上可能是话语的终止，也称为终端节点。 第二个条件是确定在再次分支之前，语音网格内的所有搜索路径都会收敛到公共节点，也称为收缩节点。 在找到任一条件后，系统可以传达部分语音识别结果。 稳定性和正确性概率也可以确定传达哪些部分结果。

公开(公告)号：US20150100316A1

公开(公告)日：2015-04-09

申请号：US14565516

申请日：2014-12-10

申请人： AT&T Intellectual Property I, L.P.

发明人： Jason D. Williams ,  Ethan SELFRIDGE

IPC分类号： G10L15/22 ,  G10L15/06 ,  G10L15/05

CPC分类号： G10L15/222 ,  G10L15/04 ,  G10L15/05 ,  G10L15/063 ,  G10L15/083

摘要： Disclosed herein are systems, methods, and non-transitory computer-readable storage media for advanced turn-taking in an interactive spoken dialog system. A system configured according to this disclosure can incrementally process speech prior to completion of the speech utterance, and can communicate partial speech recognition results upon finding particular conditions. A first condition which, if found, allows the system to communicate partial speech recognition results, is that the most recent word found in the partial results is statistically likely to be the termination of the utterance, also known as a terminal node. A second condition is the determination that all search paths within a speech lattice converge to a common node, also known as a pinch node, before branching out again. Upon finding either condition, the system can communicate the partial speech recognition results. Stability and correctness probabilities can also determine which partial results are communicated.

摘要翻译： 这里公开了用于交互式口语对话系统中的高级转弯的系统，方法和非暂时的计算机可读存储介质。 根据本公开配置的系统可以在完成语音话语之前递增地处理语音，并且可以在发现特定条件时传送部分语音识别结果。 如果发现，允许系统传达部分语音识别结果的第一个条件是，在部分结果中发现的最新字词在统计上可能是话语的终止，也称为终端节点。 第二个条件是确定在再次分支之前，语音网格内的所有搜索路径都会收敛到公共节点，也称为收缩节点。 在找到任一条件后，系统可以传达部分语音识别结果。 稳定性和正确性概率也可以确定传达哪些部分结果。

公开(公告)号：US08954319B2

公开(公告)日：2015-02-10

申请号：US14338550

申请日：2014-07-23

申请人： AT&T Intellectual Property I, L.P.

发明人： Jason D. Williams

IPC分类号： G06F17/27 ,  G10L15/00 ,  G10L15/18 ,  G10L21/00 ,  G10L19/00 ,  G06F15/18 ,  G06F17/28 ,  G10L15/06

CPC分类号： G10L15/063 ,  G06F17/2881

摘要： Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for generating a natural language spoken dialog system. The method includes nominating a set of allowed dialog actions and a set of contextual features at each turn in a dialog, and selecting an optimal action from the set of nominated allowed dialog actions using a machine learning algorithm. The method includes generating a response based on the selected optimal action at each turn in the dialog. The set of manually nominated allowed dialog actions can incorporate a set of business rules. Prompt wordings in the generated natural language spoken dialog system can be tailored to a current context while following the set of business rules. A compression label can represent at least one of the manually nominated allowed dialog actions.

摘要翻译： 本文公开了用于生成自然语言对话系统的系统，计算机实现的方法和有形的计算机可读存储介质。 该方法包括在对话中的每个转弯处提取一组允许的对话动作和一组上下文特征，以及使用机器学习算法从该组指定的允许对话动作中选择最佳动作。 该方法包括在对话中的每一回合基础上产生基于所选择的最佳动作的响应。 一组手动提名的允许的对话框操作可以包含一组业务规则。 生成的自然语言对话系统中的提示字词可以根据当前上下文进行定制，同时遵循一组业务规则。 压缩标签可以表示手动指定的允许对话动作中的至少一个。