This paper describes a novel modification of Histogram Equalization (HEQ) approach to robust speech recognition. We propose separate equalization of the high frequency (HF) and low frequency (LF) bands. We study different combinations of the sub-band equalization and obtain best results when we perform a two-stage equalization. First, conventional HEQ is performed on the cepstral features, which does not completely equalize HF and LF bands, even though the overall histogram equalization is good. In the second stage, an equalization is done separately on the HF and the LF 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 in WER on Aurora-2 and Aurora-4 databases respectively.
Cite as: Joshi, V., Bilgi, R., Umesh, S., Garcia, L., Benitez, C. (2011) Sub-band level histogram equalization for robust speech recognition. Proc. Interspeech 2011, 1661-1664, doi: 10.21437/Interspeech.2011-213
@inproceedings{joshi11_interspeech,
author={Vikas Joshi and Raghavendra Bilgi and S. Umesh and L. Garcia and C. Benitez},
title={{Sub-band level histogram equalization for robust speech recognition}},
year=2011,
booktitle={Proc. Interspeech 2011},
pages={1661--1664},
doi={10.21437/Interspeech.2011-213}
}