Combining speaker and noise feature normalization techniques for Automatic Speech Recognition

Author

Garcia, Luis ; Benitez, Carmen ; Segura, J.C. ; Umesh, S.

Author_Institution

Dept. of Signal Theory, Telematics & Commun., Univ. of Granada, Granada, Spain

fYear

2011

fDate

22-27 May 2011

Firstpage

5496

Lastpage

5499

Abstract

This work deals with strategies to jointly reduce the speaker and environment mismatches in Automatic Speech Recognition. The consequences of environmental mismatch in the performance of conventional Vocal Tract Length Normalization algorithm are analyzed, observing the sensitivity of the warping factor distributions to the SNR fall. A new combined speaker-noise normalization strategy which reduces the effect of noise in VTLN by applying Histogram Equalization is proposed and experimented in AURORA2 and AU RORA4 databases. Solid results are obtained and discussed to analyze the effectiveness of the described technique.

Keywords

speaker recognition; speech recognition; AU- RORA4 database; AURORA2 database; SNR; VTLN; automatic speech recognition; combined speaker-noise normalization strategy; histogram equalization; noise feature normalization techniques; vocal tract length normalization algorithm; Databases; Hidden Markov models; Signal to noise ratio; Speech; Speech recognition; Training; Combined Strategies; HEQ; Noise Reduction; Speaker Normalization; VTLN;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on

Conference_Location

Prague

ISSN

1520-6149

Print_ISBN

978-1-4577-0538-0

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2011.5947603

Filename

5947603