公开(公告)号：WO2014197303A1

公开(公告)日：2014-12-11

申请号：PCT/US2014/040168

申请日：2014-05-30

Applicant: MICROSOFT CORPORATION

Inventor： CHANG, Shuangyu ,  LEVIT, Michael

IPC: G10L15/32 ,  G10L15/19

CPC classification number: G10L15/065 ,  G10L15/02 ,  G10L15/063 ,  G10L15/19 ,  G10L15/32

Abstract: A received utterance is recognized using different language models. For example, recognition of the utterance is independently performed using a baseline language model (BLM) and using an adapted language model (ALM). A determination is made as to what results from the different language model are more likely to be accurate. Different features may be used to assist in making the determination (e.g. language model scores, recognition confidences, acoustic model scores, quality measurements, ) may be used. A classifier may be trained and then used in determining whether to select the results using the BLM or to select the results using the ALM. A language model may be automatically trained or re-trained that adjusts a weight of the training data used in training the model in response to differences between the two results obtained from applying the different language models.

Abstract translation: 使用不同的语言模型识别接收的话语。 例如，使用基准语言模型（BLM）和使用适应语言模型（ALM）来独立地执行语音的识别。 确定不同语言模型的结果更有可能是准确的。 可以使用不同的特征来辅助确定（例如，语言模型分数，识别信心，声学模型评分，质量测量）。 可以对分类器进行训练，然后用于确定是使用BLM选择结果还是使用ALM选择结果。 可以自动训练或重新训练语言模型，以响应于从应用不同语言模型获得的两个结果之间的差异来调整用于训练模型的训练数据的权重。

公开(公告)号：WO2010141513A2

公开(公告)日：2010-12-09

申请号：PCT/US2010/036964

申请日：2010-06-01

Applicant: MICROSOFT CORPORATION

Inventor： CHANG, Shuangyu ,  LEVIT, Michael ,  BUNTSCHUH, Bruce

IPC: G06F17/00 ,  G06F17/18 ,  G06F17/27 ,  G06F15/16 ,  G06F13/14

CPC classification number: G06N99/005 ,  G10L15/08 ,  G10L15/19 ,  G10L15/32 ,  G10L2015/228

Abstract: Architecture that employs an overall grammar as a set of context-specific grammars for recognition of an input, each responsible for a specific context, such as subtask category, geographic region, etc. The grammars together cover the entire domain. Moreover, multiple recognitions can be run in parallel against the same input, where each recognition uses one or more of the context-specific grammars. The multiple intermediate recognition results from the different recognizer-grammars are reconciled by running re-recognition using a dynamically composed grammar based on the multiple recognition results and potentially other domain knowledge, or selecting the winner using a statistical classifier operating on classification features extracted from the multiple recognition results and other domain knowledge.

Abstract translation: 使用整体语法作为一组上下文特定语法的体系结构，用于识别输入，每个语言负责特定上下文，例如子任务类别，地理区域等。语法一起涵盖整个域。 此外，可以针对相同的输入并行运行多个识别，其中每个识别使用一个或多个上下文特定语法。 通过使用基于多个识别结果和潜在的其他领域知识的动态组合语法运行重新识别来协调来自不同识别器语法的多个中间识别结果，或者使用对从分类特征提取的分类特征进行运算的统计分类器来选择胜者 多重识别结果等领域知识。