公开(公告)号：WO2008089470A1

公开(公告)日：2008-07-24

申请号：PCT/US2008/051584

申请日：2008-01-21

Applicant: MICROSOFT CORPORATION

Inventor： YAMAN, Sibel ,  DENG, Li ,  YU, Dong ,  WANG, Ye-yi ,  ACERO, Alejandro

IPC: G10L15/08

CPC classification number: G10L15/1815

Abstract: A novel system integrates speech recognition and semantic classification, so that acoustic scores in a speech recognizer that accepts spoken utterances may be taken into account when training both language models and semantic classification models. For example, a joint association score may be defined that is indicative of a correspondence of a semantic class and a word sequence for an acoustic signal. The joint association score may incorporate parameters such as weighting parameters for signal-to-class modeling of the acoustic signal, language model parameters and scores, and acoustic model parameters and scores. The parameters may be revised to raise the joint association score of a target word sequence with a target semantic class relative to the joint association score of a competitor word sequence with the target semantic class. The parameters may be designed so that the semantic classification errors in the training data are minimized.

Abstract translation: 一种新颖的系统集成了语音识别和语义分类，从而在训练语言模型和语义分类模型时，可以考虑接受讲话语音的语音识别器中的声学分数。 例如，可以定义联合关联分数，其表示声学信号的语义类别和单词序列的对应关系。 联合关联评分可以包括参数，例如声信号的信号到类建模的加权参数，语言模型参数和分数，以及声学模型参数和分数。 可以修改参数以相对于具有目标语义类的竞争者词序列的联合关联分数来提高目标词序列与目标语义类别的联合关联分数。 参数可以被设计成使训练数据中的语义分类误差最小化。