计算机工程2017，Vol.43Issue(3)：220-224,5.DOI:10.3969/j.issn.1000-3428.2017.03.037
基于噪声分类与补偿的车载语音识别
Vehicular Speech Recognition Based on Noise Classification and Compensation
摘要
Abstract
Focusing on the issue that the robustness of the existing vehicular speech recognition system degrades drastically under practical application environments,a noise classification and compensation method based on Support Vector Machine(SVM) is proposed.Firstly,the noise of each application scene is collected to construct the SVM noise classifier which is used to classify the noise in the mute segment of the speech signal,and the corresponding noise training template is selected according to the noise type.The Delta-Spectral Cepstral Coefficients(DSCC) is used as the characteristic parameter,further suppresses the noise in the speech segment for vehicle speech recognition system.Experimental results show that the proposed method can effectively improve the noise robustness of vehicle speech recognition system and has higher speech recognition rate than sparse coded speech enhancement and PNCC feature enhancement methods.关键词
语音识别/噪声鲁棒性/噪声补偿/支持向量机/特征提取Key words
speech recognition/noise robustness/noise compensation/Support Vector Machine(SVM)/feature extraction分类
信息技术与安全科学引用本文复制引用
项秉伟,景新幸,杨海燕..基于噪声分类与补偿的车载语音识别[J].计算机工程,2017,43(3):220-224,5.基金项目
广西自然科学基金(2012GXNSFAA053221) （2012GXNSFAA053221）
广西千亿元产业产学研用合作项目(信科院0168). （信科院0168）
