ETRW on Speech Processing in Adverse Conditions Cannes-Mandelieu, France November 10-13, 1992

AR modelling of the speech autocorrelation to improve noisy speech recognition

J. Hernando, Climent Nadeu

Department of Signal Theory and Communications, Polytechnical University of Catalonia, Barcelona, Spain

Speech recognition in noisy environments remains an unsolved problem even in the case of isolated word recognition with small vocabularies. Recently, several techniques have been proposed to alleviate this problem. Concretely, two closely related parameterization techniques based on an AR modelling in the autocorrelation domain called SMC and OSALPC have shown good results using speech contaminated by additive white noise. The aim of this paper is twofold: to compare several techniques based on an AR modelling in the autocorrelation domain, including SMC and OSALPC, and to find the optimum model order and cepstral liftering for noisy conditions.

Full Paper

Bibliographic reference.  Hernando, J. / Nadeu, Climent (1992): "AR modelling of the speech autocorrelation to improve noisy speech recognition", In SPAC-1992, 107-110.