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| 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. |
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