Comparative Evaluation of Single-Channel MMSE-Based Noise Reduction Schemes for Speech Recognition

One of the big challenges in the field of Automatic Speech Recognition (ASR) consists in developing suitable solutions able to work properly also in adverse acoustic conditions, like in presence of additive noise and/or in reverberant rooms. Recently a certain attention has been paid to deeply integ...

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Bibliographic Details
Main Authors: Emanuele Principi, Simone Cifani, Rudy Rotili, Stefano Squartini, Francesco Piazza
Format: Article
Language:English
Published: Wiley 2010-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2010/962103
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Summary:One of the big challenges in the field of Automatic Speech Recognition (ASR) consists in developing suitable solutions able to work properly also in adverse acoustic conditions, like in presence of additive noise and/or in reverberant rooms. Recently a certain attention has been paid to deeply integrate the noise suppressor in the feature extraction pipeline. In this paper, different single-channel MMSE-based noise reduction schemes have been implemented both in the frequency and cepstral domains and the related recognition performances evaluated on the AURORA2 and AURORA4 databases, therefore providing a useful reference for the scientific community.
ISSN:2090-0147
2090-0155