Speech recognition in impulsive noise

Vaseghi, S. V. and Milner, B. P. (1995) Speech recognition in impulsive noise. In: IEEE International Conference on Acoustics Speech Signal Processing (ICASSP), 1995-05-09 - 1995-05-12.

Full text not available from this repository. (Request a copy)

Abstract

This paper presents experimental results on the use of noise compensation schemes with hidden Markov model (HMM) speech recognition systems operating in the presence of impulsive noise. A measure of signal to impulsive noise ratio is introduced, and the effects of varying the percentage of impulsive noise contamination, and the power of impulsive noise, on speech recognition are investigated. For the modelling of an impulsive noise process, an amplitude-modulated binary sequence model and a binary-state HMM are considered. For impulsive noise compensation a front-end method and a noise-adaptive method are evaluated. Experiments demonstrate that the noise compensation methods achieve a substantial improvement in speech recognition accuracy across a wide range of signal to impulsive noise ratios.

Item Type:	Conference or Workshop Item (Other)
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Visual Computing and Signal Processing Faculty of Science > Research Groups > Smart Emerging Technologies (former - to 2025) Faculty of Science > Research Groups > Data Science and AI
Depositing User:	EPrints Services
Date Deposited:	01 Oct 2010 13:41
Last Modified:	28 Mar 2025 13:27
URI:	https://ueaeprints.uea.ac.uk/id/eprint/2989
DOI:	10.1109/ICASSP.1995.479622

Actions (login required)

View Item