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1. 发明授权

US08972256B2 System and method for dynamic noise adaptation for robust automatic speech recognition 有权
标题翻译：用于鲁棒自动语音识别的动态噪声适应的系统和方法
公开(公告)号：US08972256B2
公开(公告)日：2015-03-03
申请号：US13274694
申请日：2011-10-17
申请人： Steven J. Rennie , Pierre Dognin , Petr Fousek
发明人： Steven J. Rennie , Pierre Dognin , Petr Fousek
IPC分类号： G10L15/20
CPC分类号： G10L15/20 , G10L21/0208
摘要： A speech processing method and arrangement are described. A dynamic noise adaptation (DNA) model characterizes a speech input reflecting effects of background noise. A null noise DNA model characterizes the speech input based on reflecting a null noise mismatch condition. A DNA interaction model performs Bayesian model selection and re-weighting of the DNA model and the null noise DNA model to realize a modified DNA model characterizing the speech input for automatic speech recognition and compensating for noise to a varying degree depending on relative probabilities of the DNA model and the null noise DNA model.
摘要翻译：描述语音处理方法和布置。动态噪声适应（DNA）模型表征反映背景噪声影响的语音输入。空噪声DNA模型基于反映空值噪声不匹配条件来表征语音输入。 DNA相互作用模型执行贝叶斯模型选择和重新加权DNA模型和空值噪声DNA模型，以实现表征语音输入的修改后的DNA模型，用于自动语音识别，并根据相对概率对不同程度的噪声进行补偿 DNA模型和无效噪声DNA模型。

2. 发明申请

US20120150536A1 MODEL RESTRUCTURING FOR CLIENT AND SERVER BASED AUTOMATIC SPEECH RECOGNITION 失效
标题翻译：基于客户端和服务器的自动语音识别的模型重构
公开(公告)号：US20120150536A1
公开(公告)日：2012-06-14
申请号：US12964433
申请日：2010-12-09
申请人： Pierre Dognin , Vaibhava Goel , John R. Hershey , Peder A. Olsen
发明人： Pierre Dognin , Vaibhava Goel , John R. Hershey , Peder A. Olsen
IPC分类号： G10L15/00
CPC分类号： G10L15/144 , G10L15/30 , G10L2015/0636 , G10L2015/085
摘要： Access is obtained to a large reference acoustic model for automatic speech recognition. The large reference acoustic model has L states modeled by L mixture models, and the large reference acoustic model has N components. A desired number of components Nc, less than N, to be used in a restructured acoustic model derived from the reference acoustic model, is identified. The desired number of components Nc is selected based on a computing environment in which the restructured acoustic model is to be deployed. The restructured acoustic model also has L states. For each given one of the L mixture models in the reference acoustic model, a merge sequence is built which records, for a given cost function, sequential mergers of pairs of the components associated with the given one of the mixture models. A portion of the Nc components is assigned to each of the L states in the restructured acoustic model. The restructured acoustic model is built by, for each given one of the L states in the restructured acoustic model, applying the merge sequence to a corresponding one of the L mixture models in the reference acoustic model until the portion of the Nc components assigned to the given one of the L states is achieved.
摘要翻译：获得用于自动语音识别的大参考声学模型。大参考声学模型具有由L个混合模型建模的L状态，并且大的参考声学模型具有N个分量。识别在从参考声学模型导出的重构声学模型中使用的期望数量的小于N的分量Nc。基于要重新组织的声学模型要部署的计算环境来选择所需数量的分量Nc。重组的声学模型也有L个状态。对于参考声学模型中的每个给定的一个L混合模型，构建合并序列，其针对给定的成本函数记录与给定的混合模型相关联的成分对的顺序合并。 Nc分量的一部分被分配给重构的声学模型中的每个L状态。重构的声学模型由重构的声学模型中的每个给定的一个L状态构建，将合并序列应用于参考声学模型中的L个混合模型中的对应的一个，直到分配给给出了一个L状态。

3. 发明授权

US08635067B2 Model restructuring for client and server based automatic speech recognition 失效
标题翻译：基于客户端和服务器的自动语音识别模型重组
公开(公告)号：US08635067B2
公开(公告)日：2014-01-21
申请号：US12964433
申请日：2010-12-09
申请人： Pierre Dognin , Vaibhava Goel , John R. Hershey , Peder A. Olsen
发明人： Pierre Dognin , Vaibhava Goel , John R. Hershey , Peder A. Olsen
IPC分类号： G10L15/14
CPC分类号： G10L15/144 , G10L15/30 , G10L2015/0636 , G10L2015/085
摘要： Access is obtained to a large reference acoustic model for automatic speech recognition. The large reference acoustic model has L states modeled by L mixture models, and the large reference acoustic model has N components. A desired number of components Nc, less than N, to be used in a restructured acoustic model derived from the reference acoustic model, is identified. The desired number of components Nc is selected based on a computing environment in which the restructured acoustic model is to be deployed. The restructured acoustic model also has L states. For each given one of the L mixture models in the reference acoustic model, a merge sequence is built which records, for a given cost function, sequential mergers of pairs of the components associated with the given one of the mixture models. A portion of the Nc components is assigned to each of the L states in the restructured acoustic model. The restructured acoustic model is built by, for each given one of the L states in the restructured acoustic model, applying the merge sequence to a corresponding one of the L mixture models in the reference acoustic model until the portion of the Nc components assigned to the given one of the L states is achieved.
摘要翻译：获得用于自动语音识别的大参考声学模型。大参考声学模型具有由L个混合模型建模的L状态，并且大的参考声学模型具有N个分量。识别在从参考声学模型导出的重构声学模型中使用的期望数量的小于N的分量Nc。基于要重新组织的声学模型要部署的计算环境来选择所需数量的分量Nc。重组的声学模型也有L个状态。对于参考声学模型中的每个给定的一个L混合模型，构建合并序列，其针对给定的成本函数记录与给定的混合模型相关联的成分对的顺序合并。 Nc分量的一部分被分配给重构的声学模型中的每个L状态。重构的声学模型由重构的声学模型中的每个给定的一个L状态构建，将合并序列应用于参考声学模型中的L个混合模型中的对应的一个，直到分配给给出了一个L状态。

4. 发明申请

US20130096915A1 System and Method for Dynamic Noise Adaptation for Robust Automatic Speech Recognition 有权
公开(公告)号：US20130096915A1
公开(公告)日：2013-04-18
申请号：US13274694
申请日：2011-10-17
申请人： Steven J. Rennie , Pierre Dognin , Petr Fousek
发明人： Steven J. Rennie , Pierre Dognin , Petr Fousek
IPC分类号： G10L15/20
CPC分类号： G10L15/20 , G10L21/0208
摘要： A speech processing method and arrangement are described. A dynamic noise adaptation (DNA) model characterizes a speech input reflecting effects of background noise. A null noise DNA model characterizes the speech input based on reflecting a null noise mismatch condition. A DNA interaction model performs Bayesian model selection and re-weighting of the DNA model and the null noise DNA model to realize a modified DNA model characterizing the speech input for automatic speech recognition and compensating for noise to a varying degree depending on relative probabilities of the DNA model and the null noise DNA model.

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