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Recognition of speech in additive and convolutional noise based on RASTA spectral processing

Authors:

Hynek Hermansky, Nelson Morgan, and Hans-Günter Hirsch

Book Title:

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

Volume:

2

Venue:

Minneapolis, MN, USA

Date:

Apr. 1993

Pages:

83–86

Language:

English

Abstract

RASTA (relative spectral) processing is studied in a spectral domain which is linear-like for small spectral values and logarithmic-like for large spectral values. Experiments with a recognizer trained on clean speech and test data degraded by both convolutional and additive noise show that doing RASTA processing in the new domain yields results comparable with those obtained by training the recognizer on known noise

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