Non-stationary feature extraction for automatic speech recognition

Author

Tüske, Zoltán ; Golik, Pavel ; Schlüter, Ralf ; Drepper, Friedhelm R.

Author_Institution

Comput. Sci. Dept., RWTH Aachen Univ., Aachen, Germany

fYear

2011

fDate

22-27 May 2011

Firstpage

5204

Lastpage

5207

Abstract

In current speech recognition systems mainly Short-Time Fourier Transform based features like MFCC are applied. Dropping the short-time stationarity assumption of the voiced speech, this paper introduces the non-stationary signal analysis into the ASR framework. We present new acoustic features extracted by a pitch-adaptive Gammatone filter bank. The noise robustness was proved on AURORA 2 and 4 tasks, where the proposed features outperform the standard MFCC. Furthermore, successful combination experiments via ROVER indicate the differences between the new features and MFCC.

Keywords

adaptive filters; feature extraction; filtering theory; speech recognition; ASR framework; MFCC; ROVER; automatic speech recognition; nonstationary feature extraction; pitch-adaptive Gammatone filter bank; short-time Fourier transform; Feature extraction; Harmonic analysis; Mel frequency cepstral coefficient; Speech; Speech recognition; Time frequency analysis; Gammachirp; Gammatone; non-stationary; pitch-adaptive;

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.2011.5947530

Filename

5947530