Speaker verification in noisy environment using missing feature approach

Authors:
Dayana Ribas;Jesús A. Villalba;Eduardo Lleida;José R. Calvo
Affiliations:
Advanced Technologies Application Center, La Habana, Cuba;Communications Technology Group, Aragon Institute for Engineering Research, University of Zaragoza, Spain;Communications Technology Group, Aragon Institute for Engineering Research, University of Zaragoza, Spain;Advanced Technologies Application Center, La Habana, Cuba
Venue:
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Year:
2010

Citing 3
Cited 0

On noise masking for automatic missing data speech recognition: A survey and discussion

Computer Speech and Language
Noise Reduction in Speech Processing

Noise Reduction in Speech Processing
Robust Speaker Recognition in Noisy Conditions

IEEE Transactions on Audio, Speech, and Language Processing

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Abstract

In order to handle speech signals corrupted by noise in speaker verification and provide robustness to systems, this paper evaluates the use of missing feature (MF) approach with a novel combination of techniques. A mask estimation based on spectral subtraction is used to determine the reliability of spectral components in a speech signal corrupted by noise. A cluster based reconstruction technique is used to remake the damaged spectrum. The verification performance was evaluated through a speaker verification experiment with signals corrupted by white noise under different signal to noise ratios. The results were promising since they reflected a relevant increase of speaker verification performance, applyingMF approach with this combination of techniques.