September 22-25, 1997
To improve the robustness of speech recognition in additive noisy environments, an SVD based space transformation approach is proposed. It is shown that with this approach, not only the signal-to-noise ratio is improved but also a significant recognition error reduction is achieved. A multiple model based on the proposed method is developed and it can provide high recognition rate for a large range of SNRs. Recognition experiments on a speaker-dependent mono-syllabic database with additive noise show that, this new approach outperforms LPC cepstrum, MFCC, and OSALPC cepstrum significantly.
Bibliographic reference. Guan, Cun-tai / Leung, Shu-hung / Lau, Wing-hong (1997): "A space transformation approach for robust speech recognition in noisy environments", In EUROSPEECH-1997, 1591-1594.