comparative evaluation of single-channel mmse-based noise reduction schemes for speech recognition

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ID: 255225
2010
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Abstract
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.
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principi2010journalcomparative Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Emanuele Principi;Simone Cifani;Rudy Rotili;Stefano Squartini;Francesco Piazza
Journal Molecular diversity
Year 2010
DOI
10.1155/2010/962103
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