| Paper: | SP-L9.3 | ||
| Session: | Robust Features for Speech Recognition | ||
| Time: | Friday, May 21, 13:40 - 14:00 | ||
| Presentation: | Lecture | ||
| Topic: | Speech Processing: Robust Speech Recognition | ||
| Title: | ROBUSTNESS OF SPEECH RECOGNITION USING GENETIC ALGORITHMS AND A MEL-CEPSTRAL SUBSPACE APPROACH | ||
| Authors: | Sid-Ahmed Selouani; Université de Moncton | ||
| Douglas O'Shaughnessy; INRS-EMT | |||
| Abstract: | This paper presents a method to compensate cepstral coefficients (MFCCs) for a HMM-based speech recognition system evolving under telephone-channel degradations. The technique we propose is based on the combination of the Karhonen-Loève Transform (KLT) and Genetic Algorithms (GA). The idea consists of projecting the band-limited MFCCs onto a subspace generated by the genetically optimized KLT principal axes. Experiments show a clear improvement when the method was applied to the NTIMIT telephone speech database. Word recognition results obtained on the HTK toolkit platform using N-mixture tri-phone models and a bigram language model are presented and discussed. | ||
| Back | |||
Home -||-
Organizing Committee -||-
Technical Committee -||-
Technical Program -||-
Plenaries
Paper Submission -||-
Special Sessions -||-
ITT -||-
Paper Review -||-
Exhibits -||-
Tutorials
Information -||-
Registration -||-
Travel Insurance -||-
Housing -||-
Workshops