语音识别错误的分类分析  

Classification analysis of speech recognition errors

作　　者：付跃文[1] 杜利民[1] 

机构地区：[1]中国科学院声学研究所,北京100080

出　　处：《计算机应用》2005年第2期291-293,共3页journal of Computer Applications

基　　金：国家 973计划项目(G1998030505)

摘　　要：大词表连续语音识别系统由多个组件构成,识别错误受多种因素的影响。系统开发者需要分析错误发生的不同原因。根据语音识别的基本理论给出了对错误进行分类分析的原理,将识别错误按错误原因分为解码错误、声学模型错误、语言模型错误、声学和语言复合错误四大类,并对分类后的错误做了统计分析。实验证明,识别错误的分类分析为系统的改进提供了参考依据。Large vocabulary continuous speech recognition system consists of several components, and recognition errors are caused by different factors. Developers need to know how the errors occur. In this paper we deduced the principle to classify the recognition errors from the recognition theory and put each error according to its cause into one of four classes: the decoding, the acoustic model, the language model, and the acoustic and language model. We then performed statistical analysis of classified errors. Experiments show that classification analysis of recognition errors provides guidance for improving the system.

关 键 词：大词表连续语音识别 识别错误 分类 

分 类 号：TP391.42[自动化与计算机技术—计算机应用技术]