A comparison of front-end configurations for robust speech recognition

Research output: Contribution to conferenceOther

43 Citations (Scopus)

Abstract

This paper presents a comparative analysis of the processing stages involved in feature extraction for speech recognition. Feature extraction is considered as comprising three different processing stages; namely static feature extraction, normalisation and inclusion of temporal information. In each stage a comparison of techniques is made, both theoretically and in terms of their comparative performance. The analysis shows that while some techniques may appear significantly different, upon analysis the effect they have on the signal can be similar. Comparative studies include MFCC and PLP analysis, RASTA filtering and cepstral mean normalisation, and temporal derivatives and cepstral-time matrices. Experimental results, on an unconstrained monophone task, compare recognition performance using different front-end configurations.
Original languageEnglish
DOIs
Publication statusPublished - May 2002
EventIEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) - Minneapolis, United States
Duration: 13 May 200217 May 2002

Conference

ConferenceIEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)
Country/TerritoryUnited States
CityMinneapolis
Period13/05/0217/05/02

Cite this