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  • Noise Compensation in a Multi-Modal Verification System

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    18477_1.pdf (381.3Kb)
    Author(s)
    Sanderson, C
    Paliwal, KK
    Griffith University Author(s)
    Paliwal, Kuldip K.
    Year published
    2001
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    Abstract
    In this paper we propose an adaptive multi-modal verification system comprised of a modified Minimum Cost Bayesian Classifier (MCBC) and a method to find the reliability of the speech expert for various noisy conditions. The modified MCBC takes into account the reliability of each modality expert, allowing the de-emphasis of the contribution of opinions from the expert affected by noise. Reliability of the speech expert is found without directly modeling the noisy speech or finding the reliability a priori for various conditions of the speech signal. Experiments on the Digit Database show the Total Error (TE) to ...
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    In this paper we propose an adaptive multi-modal verification system comprised of a modified Minimum Cost Bayesian Classifier (MCBC) and a method to find the reliability of the speech expert for various noisy conditions. The modified MCBC takes into account the reliability of each modality expert, allowing the de-emphasis of the contribution of opinions from the expert affected by noise. Reliability of the speech expert is found without directly modeling the noisy speech or finding the reliability a priori for various conditions of the speech signal. Experiments on the Digit Database show the Total Error (TE) to be reduced by 78% when compared to a non-adaptive system.
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    Conference Title
    2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS
    Volume
    1
    Publisher URI
    http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7486
    DOI
    https://doi.org/10.1109/ICASSP.2001.940791
    Copyright Statement
    © 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    Publication URI
    http://hdl.handle.net/10072/1266
    Collection
    • Conference outputs

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