Sub-band level histogram equalization for robust speech recognition

Abstract

This paper describes a novel modification of Histogram Equalization approach to robust speech recognition. We propose separate equalization of the high frequency and low frequency bands. We study different combinations of the sub-band equalization and obtain best results when we performs a twostage equalization. First, conventional Histogram Equalization (HEQ) is performed on the cepstral features, which does not completely equalize high frequency and low frequency bands, even though the overall histogram equalization is good. In the second stage, an equalization is done separately on the high frequency and the low frequency components of the above equalized cepstra. We refer to this approach as Sub-band Histogram Equalization (S-HEQ). The new set of features has better equalization of the sub-bands as well as the overall cepstral histogram. Recognition results show a relative improvement of 12% and 15% over conventional HEQ on Aurora-2 and Aurora4 databases respectively.