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Speaker verification under degraded condition: a perceptual study

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Abstract

This study analyzes the effect of degradation on human and automatic speaker verification (SV) tasks. The perceptual test is conducted by the subjects having knowledge about speaker verification. An automatic SV system is developed using the Mel-frequency cepstral coefficients (MFCC) and Gaussian mixture model (GMM). The human and automatic speaker verification performances are compared for clean train and different degraded test conditions. Speech signals are reconstructed in clean and degraded conditions by highlighting different speaker specific information and compared through perceptual test. The perceptual cues that the human subjects used as speaker specific information are investigated and their importance in degraded condition is highlighted. The difference in the nature of human and automatic SV tasks is investigated in terms of falsely accepted and falsely rejected speech pairs. Speech signals are reconstructed in clean and degraded conditions by highlighting different speaker specific information and compared through perceptual test. A discussion on human vs automatic speaker verification is carried out and the possibility of performance improvement of automatic speaker verification under degraded condition is suggested.

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Authors and Affiliations

  1. Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, India

    Gayadhar Pradhan & S. R. Mahadeva Prasanna

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  1. Gayadhar Pradhan
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  2. S. R. Mahadeva Prasanna
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Correspondence to S. R. Mahadeva Prasanna.

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Pradhan, G., Prasanna, S.R.M. Speaker verification under degraded condition: a perceptual study. Int J Speech Technol 14, 405–417 (2011). https://doi.org/10.1007/s10772-011-9120-6

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  • DOI: https://doi.org/10.1007/s10772-011-9120-6

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