Recognizing reverberant speech with RASTA-PLP

Author

Kingsbury, Brian E D ; Morgan, Nelson

Author_Institution

Int. Comput. Sci. Inst., Berkeley, CA, USA

Volume

2

fYear

1997

fDate

21-24 Apr 1997

Firstpage

1259

Abstract

The performance of the PLP (perceptual linear predictive), log-RASTA-PLP, and J-RASTA-PLP front ends for recognition of highly reverberant speech is measured and compared with the performance of humans and the performance of an experimental RASTA-like front end on reverberant speech, and with the performance of a PLP-based recognizer trained on reverberant speech. While humans are able to reliably recognize the reverberant test set, achieving a 6.1% word error rate, the best RASTA-PLP-based recognizer has a word error rate of 68.7% on the same test set, and the PLP-based recognizer trained on reverberant speech has a 50.3% word error rate. Our experimental variant on RASTA processing provides a statistically significant improvement in performance on the reverberant speech, with a best word error rate of 64.1%

Keywords

error statistics; prediction theory; reverberation; speech recognition; J-RASTA-PLP front end; PLP front end; PLP-based recognizer; highly reverberant speech recognition; log-RASTA-PLP front end; perceptual linear predictive front end; performance; word error rate; Additive noise; Automatic speech recognition; Computer science; Error analysis; Humans; Reverberation; Speech analysis; Speech enhancement; Speech recognition; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on

Conference_Location

Munich

ISSN

1520-6149

Print_ISBN

0-8186-7919-0

Type

conf

DOI

10.1109/ICASSP.1997.596174

Filename

596174