asr systems in noisy environment: analysis and solutions for increasing noise robustness

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ID: 231454
2011
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Ranked #56 of 100 articles by views in molecular therapy : the journal of the american society of gene therapy

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Abstract
This paper deals with the analysis of Automatic Speech Recognition (ASR) suitable for usage within noisy environment and suggests optimum configuration under various noisy conditions. The behavior of standard parameterization techniques was analyzed from the viewpoint of robustness against background noise. It was done for Melfrequency cepstral coefficients (MFCC), Perceptual linear predictive (PLP) coefficients, and their modified forms combining main blocks of PLP and MFCC. The second part is devoted to the analysis and contribution of modified techniques containing frequency-domain noise suppression and voice activity detection. The above-mentioned techniques were tested with signals in real noisy environment within Czech digit recognition task and AURORA databases. Finally, the contribution of special VAD selective training and MLLR adaptation of acoustic models were studied for various signal features.
Reference Key
rajnoha2011radioengineeringasr Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;J. Rajnoha;P. Pollak
Journal molecular therapy : the journal of the american society of gene therapy
Year 2011
DOI
DOI not found
URL
www.radioeng.cz/fulltexts/2011/11_01_074_084.pdf
Keywords
feature extraction electronics nuclear engineering

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