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1. 发明授权

US07877256B2 Time synchronous decoding for long-span hidden trajectory model 有权
标题翻译：长跨隐藏轨迹模型的时间同步解码
公开(公告)号：US07877256B2
公开(公告)日：2011-01-25
申请号：US11356905
申请日：2006-02-17
申请人： Xiaolong Li , Li Deng , Dong Yu , Alejandro Acero
发明人： Xiaolong Li , Li Deng , Dong Yu , Alejandro Acero
IPC分类号： G10L15/14
CPC分类号： G10L15/08
摘要： A time-synchronous lattice-constrained search algorithm is developed and used to process a linguistic model of speech that has a long-contextual-span capability. In the algorithm, hypotheses are represented as traces that include an indication of a current frame, previous frames and future frames. Each frame can include an associated linguistic unit such as a phone or units that are derived from a phone. Additionally, pruning strategies can be applied to speed up the search. Further, word-ending recombination methods are developed to speed up the computation. These methods can effectively deal with an exponentially increased search space.
摘要翻译：开发了一种时间同步的格格约束搜索算法，用于处理具有长语境跨度能力的语言语言模型。在算法中，假设被表示为包括当前帧，先前帧和未来帧的指示的迹线。每个帧可以包括相关联的语言单元，例如从电话派生的电话或单元。此外，可以应用修剪策略来加快搜索速度。此外，开发了文字重组方法以加速计算。这些方法可以有效地处理指数级增加的搜索空间。

2. 发明申请

US20070198266A1 Time synchronous decoding for long-span hidden trajectory model 有权
标题翻译：长跨隐藏轨迹模型的时间同步解码
公开(公告)号：US20070198266A1
公开(公告)日：2007-08-23
申请号：US11356905
申请日：2006-02-17
申请人： Xiaolong Li , Li Deng , Dong Yu , Alejandro Acero
发明人： Xiaolong Li , Li Deng , Dong Yu , Alejandro Acero
IPC分类号： G10L15/28
CPC分类号： G10L15/08
摘要： A time-synchronous lattice-constrained search algorithm is developed and used to process a linguistic model of speech that has a long-contextual-span capability. In the algorithm, hypotheses are represented as traces that include an indication of a current frame, previous frames and future frames. Each frame can include an associated linguistic unit such as a phone or units that are derived from a phone. Additionally, pruning strategies can be applied to speed up the search. Further, word-ending recombination methods are developed to speed up the computation. These methods can effectively deal with an exponentially increased search space.
摘要翻译：开发了一种时间同步的格格约束搜索算法，用于处理具有长语境跨度能力的语言语言模型。在算法中，假设被表示为包括当前帧，先前帧和未来帧的指示的迹线。每个帧可以包括相关联的语言单元，例如从电话派生的电话或单元。此外，可以应用修剪策略来加快搜索速度。此外，开发了文字重组方法以加速计算。这些方法可以有效地处理指数级增加的搜索空间。

3. 发明申请

US20070198260A1 Parameter learning in a hidden trajectory model 有权
标题翻译：隐藏轨迹模型中的参数学习
公开(公告)号：US20070198260A1
公开(公告)日：2007-08-23
申请号：US11356898
申请日：2006-02-17
申请人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
发明人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
IPC分类号： G10L15/00
CPC分类号： G10L15/063 , G10L2015/025
摘要： Parameters for distributions of a hidden trajectory model including means and variances are estimated using an acoustic likelihood function for observation vectors as an objection function for optimization. The estimation includes only acoustic data and not any intermediate estimate on hidden dynamic variables. Gradient ascent methods can be developed for optimizing the acoustic likelihood function.
摘要翻译：使用用于观察向量的声学似然函数作为优化的反对函数来估计包括装置和方差的隐藏轨迹模型的分布参数。该估计仅包括声学数据，而不包括对隐藏的动态变量的任何中间估计。可以开发梯度上升方法来优化声似然函数。

4. 发明授权

US08942978B2 Parameter learning in a hidden trajectory model 有权
标题翻译：隐藏轨迹模型中的参数学习
公开(公告)号：US08942978B2
公开(公告)日：2015-01-27
申请号：US13182971
申请日：2011-07-14
申请人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
发明人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
IPC分类号： G10L15/00 , G10L15/06
CPC分类号： G10L15/063 , G10L2015/025
摘要： Parameters for distributions of a hidden trajectory model including means and variances are estimated using an acoustic likelihood function for observation vectors as an objection function for optimization. The estimation includes only acoustic data and not any intermediate estimate on hidden dynamic variables. Gradient ascent methods can be developed for optimizing the acoustic likelihood function.
摘要翻译：使用用于观察向量的声学似然函数作为优化的反对函数来估计包括装置和方差的隐藏轨迹模型的分布参数。该估计仅包括声学数据，而不包括对隐藏的动态变量的任何中间估计。可以开发梯度上升方法来优化声似然函数。

5. 发明申请

US20110270610A1 PARAMETER LEARNING IN A HIDDEN TRAJECTORY MODEL 有权
标题翻译：参数学习在隐藏的TRAJECTORY模型
公开(公告)号：US20110270610A1
公开(公告)日：2011-11-03
申请号：US13182971
申请日：2011-07-14
申请人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
发明人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
IPC分类号： G10L15/00
CPC分类号： G10L15/063 , G10L2015/025
摘要： Parameters for distributions of a hidden trajectory model including means and variances are estimated using an acoustic likelihood function for observation vectors as an objection function for optimization. The estimation includes only acoustic data and not any intermediate estimate on hidden dynamic variables. Gradient ascent methods can be developed for optimizing the acoustic likelihood function.
摘要翻译：使用用于观察向量的声学似然函数作为优化的反对函数来估计包括装置和方差的隐藏轨迹模型的分布参数。该估计仅包括声学数据，而不包括对隐藏的动态变量的任何中间估计。可以开发梯度上升方法来优化声似然函数。

6. 发明授权

US08010356B2 Parameter learning in a hidden trajectory model 有权
标题翻译：隐藏轨迹模型中的参数学习
公开(公告)号：US08010356B2
公开(公告)日：2011-08-30
申请号：US11356898
申请日：2006-02-17
申请人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
发明人： Li Deng , Dong Yu , Xiaolong Li , Alejandro Acero
IPC分类号： G10L15/00
CPC分类号： G10L15/063 , G10L2015/025
摘要： Parameters for distributions of a hidden trajectory model including means and variances are estimated using an acoustic likelihood function for observation vectors as an objection function for optimization. The estimation includes only acoustic data and not any intermediate estimate on hidden dynamic variables. Gradient ascent methods can be developed for optimizing the acoustic likelihood function.
摘要翻译：使用用于观察向量的声学似然函数作为优化的反对函数来估计包括装置和方差的隐藏轨迹模型的分布参数。该估计仅包括声学数据，而不包括对隐藏的动态变量的任何中间估计。可以开发梯度上升方法来优化声似然函数。

7. 发明申请

US20080177545A1 Automatic reading tutoring with parallel polarized language modeling 有权
标题翻译：使用平行极化语言建模的自动阅读辅导
公开(公告)号：US20080177545A1
公开(公告)日：2008-07-24
申请号：US11655702
申请日：2007-01-19
申请人： Xiaolong Li , Yun-Cheng Ju , Li Deng , Alejandro Acero
发明人： Xiaolong Li , Yun-Cheng Ju , Li Deng , Alejandro Acero
IPC分类号： G10L15/28
CPC分类号： G06F17/271 , G09B17/003 , G10L15/197 , G10L2015/221
摘要： A novel system for automatic reading tutoring provides effective error detection and reduced false alarms combined with low processing time burdens and response times short enough to maintain a natural, engaging flow of interaction. According to one illustrative embodiment, an automatic reading tutoring method includes displaying a text output and receiving an acoustic input. The acoustic input is modeled with a domain-specific target language model specific to the text output, and with a general-domain garbage language model, both of which may be efficiently constructed as context-free grammars. The domain-specific target language model may be built dynamically or “on-the-fly” based on the currently displayed text (e.g. the story to be read by the user), while the general-domain garbage language model is shared among all different text outputs. User-perceptible tutoring feedback is provided based on the target language model and the garbage language model.
摘要翻译：用于自动阅读辅导的新颖系统提供了有效的错误检测和减少的假警报以及较短的处理时间负担和响应时间足够短以保持自然的，互动的互动流。根据一个说明性实施例，自动阅读辅导方法包括显示文本输出并接收声输入。声输入是用专门针对文本输出的领域特定的目标语言模型建立的，并且具有通用域垃圾语言模型，这两种语言模型都可以被有效地构建为无上下文的语法。可以基于当前显示的文本（例如，用户要阅读的故事）动态地或“即时”地构建特定领域的目标语言模型，而一般域垃圾语言模型在所有不同的方式之间共享文本输出。基于目标语言模型和垃圾语言模型提供了用户可感知的辅导反馈。

8. 发明授权

US08433576B2 Automatic reading tutoring with parallel polarized language modeling 有权
标题翻译：使用平行极化语言建模的自动阅读辅导
公开(公告)号：US08433576B2
公开(公告)日：2013-04-30
申请号：US11655702
申请日：2007-01-19
申请人： Xiaolong Li , Yun-Cheng Ju , Li Deng , Alejandro Acero
发明人： Xiaolong Li , Yun-Cheng Ju , Li Deng , Alejandro Acero
IPC分类号： G10L15/22
CPC分类号： G06F17/271 , G09B17/003 , G10L15/197 , G10L2015/221
摘要： A novel system for automatic reading tutoring provides effective error detection and reduced false alarms combined with low processing time burdens and response times short enough to maintain a natural, engaging flow of interaction. According to one illustrative embodiment, an automatic reading tutoring method includes displaying a text output and receiving an acoustic input. The acoustic input is modeled with a domain-specific target language model specific to the text output, and with a general-domain garbage language model, both of which may be efficiently constructed as context-free grammars. The domain-specific target language model may be built dynamically or “on-the-fly” based on the currently displayed text (e.g. the story to be read by the user), while the general-domain garbage language model is shared among all different text outputs. User-perceptible tutoring feedback is provided based on the target language model and the garbage language model.
摘要翻译：用于自动阅读辅导的新颖系统提供了有效的错误检测和减少的假警报以及较短的处理时间负担和响应时间足够短以保持自然的，互动的互动流。根据一个说明性实施例，自动阅读辅导方法包括显示文本输出并接收声输入。声输入是用专门针对文本输出的领域特定的目标语言模型建立的，并且具有通用域垃圾语言模型，这两种语言模型都可以被有效地构建为无上下文的语法。可以基于当前显示的文本（例如，用户要阅读的故事）动态地或“即时”地构建特定领域的目标语言模型，而一般域垃圾语言模型在所有不同的方式之间共享文本输出。基于目标语言模型和垃圾语言模型提供了用户可感知的辅导反馈。

9. 发明申请

US20090070112A1 Automatic reading tutoring 有权
标题翻译：自动阅读辅导
公开(公告)号：US20090070112A1
公开(公告)日：2009-03-12
申请号：US11900274
申请日：2007-09-11
申请人： Xiaolong Li , Li Deng , Yun-Cheng Ju , Alex Acero
发明人： Xiaolong Li , Li Deng , Yun-Cheng Ju , Alex Acero
IPC分类号： G10L15/18
CPC分类号： G10L15/18 , G09B17/003 , G10L15/183
摘要： A method of providing automatic reading tutoring is disclosed. The method includes retrieving a textual indication of a story from a data store and creating a language model including constructing a target context free grammar indicative of a first portion of the story. A first acoustic input is received and a speech recognition engine is employed to recognize the first acoustic input. An output of the speech recognition engine is compared to the language model and a signal indicative of whether the output of the speech recognition matches at least a portion of the target context free grammar is provided.
摘要翻译：公开了提供自动阅读辅导的方法。该方法包括从数据存储中检索故事的文本指示并创建包括构建指示故事的第一部分的目标上下文自由语法的语言模型。接收到第一声输入，并且采用语音识别引擎来识别第一声输入。将语音识别引擎的输出与语言模型进行比较，并且提供指示语音识别的输出是否与目标语境自由语法的至少一部分匹配的信号。

10. 发明授权

US08306822B2 Automatic reading tutoring using dynamically built language model 有权
标题翻译：使用动态内置语言模型进行自动阅读辅导
公开(公告)号：US08306822B2
公开(公告)日：2012-11-06
申请号：US11900274
申请日：2007-09-11
申请人： Xiaolong Li , Li Deng , Yun-Cheng Ju , Alex Acero
发明人： Xiaolong Li , Li Deng , Yun-Cheng Ju , Alex Acero
IPC分类号： G10L15/22
CPC分类号： G10L15/18 , G09B17/003 , G10L15/183
摘要： A method of providing automatic reading tutoring is disclosed. The method includes retrieving a textual indication of a story from a data store and creating a language model including constructing a target context free grammar indicative of a first portion of the story. A first acoustic input is received and a speech recognition engine is employed to recognize the first acoustic input. An output of the speech recognition engine is compared to the language model and a signal indicative of whether the output of the speech recognition matches at least a portion of the target context free grammar is provided.
摘要翻译：公开了提供自动阅读辅导的方法。该方法包括从数据存储中检索故事的文本指示并创建包括构建指示故事的第一部分的目标上下文自由语法的语言模型。接收到第一声输入，并且采用语音识别引擎来识别第一声输入。将语音识别引擎的输出与语言模型进行比较，并且提供指示语音识别的输出是否与目标语境自由语法的至少一部分匹配的信号。

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