Efficient Noise-Robust Speech Recognition Front-End Based on the ETSI Standard

摘要：

A powerful feature extraction system for noise robust speech recognition was standardized by ETSI.The system was developed for Distributed Speech Recognition (DSR) and includes an Advanced Front-End (AFE) to be implemented in client terminals,which send the extracted parameters to a remote server that runs a speech recognition engine.In view of the integration of a noise-robust front-end in an embedded speech recognition system,which performs simultaneously the feature extraction and the speech recognition tasks,we propose a modified implementation of the front-end with less computational requirements.Using the Aurora 2 speech database,we evaluate the impact on performance of the Blind Equalization (BE) block,the Gain Factorization (GF) block and the SNR-dependent Waveform Processing (SWP) block that are used in the AFE.We conclude that our modified front-end using Cepstral Mean Normalization (CMN) and dropping BE,GF and SWP,outperforms the AFE in a practical task.

作者: Cláudio Neves Arlindo Veiga Luís Sá Fernando Perdig(a)o

作者单位: Instituto de Telecomunicacoes,Coimbra,Portugal Instituto de Telecomunicacoes,Coimbra,Portugal;DEEC – FCTUC,University of Coimbra,Portugal

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）