Title :
A soft computing approach to improve the robustness of on-line ASR in previously unseen highly non-stationary acoustic environments
Author :
Chowdhury, Mohammad Foezur Rahman ; Selouani, Sid-Ahmed ; O´Shaughnessy, Douglas
Author_Institution :
INRS - EMT, Univ. du Quebec, Montréal, QC, Canada
Abstract :
This paper presents a soft noise compensation algorithm in the feature space to improve the noise robustness of HMM-based on-line automatic speech recognition (ASR) in unknown highly non-stationary acoustic environments. Current hard computing techniques fail to track and compensate the non-stationary noises properly in previously unseen acoustic environments. The proposed soft noise compensation algorithm is based on a joint additive background noises and channel distortions compensation (JAC) technique in feature space. In this novel soft JAC (SJAC), we use an evolutionary dynamic multi-swarm particle swarm optimization (DMS-PSO)-based soft computing (SC) technique in the front-end, and a frame synchronous bias compensation technique in the back-end of the ASR, respectively, for frame adaptive modeling and compensation of the background additive noises and channel distortions in feature space that are highly non-linear and non-Gaussian. From the experimental results, we find that the proposed evolutionary DMS-PSO-based SJAC technique achieves significant improvement in recognition performance of on-line ASR compared to our previously developed baseline Bayesian on-line spectral change point detection (BOSCPD)-based SJAC technique when evaluated over the Aurora 2 speech database.
Keywords :
Bayes methods; evolutionary computation; hidden Markov models; particle swarm optimisation; speech recognition; BOSCPD-based SJAC technique; Bayesian online spectral change point detection; DMS-PSO; HMM; additive background noises; background additive noise; channel distortions compensation; evolutionary dynamic multiswarm particle swarm optimization; feature space; frame adaptive modeling; frame synchronous bias compensation; hard computing; noise robustness; nonstationary acoustic environment; online ASR; online automatic speech recognition; soft JAC technique; soft computing; soft noise compensation algorithm; Acoustics; Additive noise; Hidden Markov models; Noise measurement; Signal to noise ratio; Speech; BOSCPD; MCRA; PSO; Soft computing; dynamic multi-swarm PSO; frame adaptive bias compensation; global optima; hard computing; noise robustness; non-stationary noise; on-line ASR; soft JAC; soft adaptive filter;
Conference_Titel :
Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4673-0381-1
Electronic_ISBN :
978-1-4673-0380-4
DOI :
10.1109/ISSPA.2012.6310607