Speaker adaptive confidence scoring using Bayesian combining

Tae Yoon Kim, Hanseok Ko

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Bayesian combining of confidence measures is proposed for speech recognition. Bayesian combining is achieved by the estimation of joint pdf of confidence feature vector in correct and incorrect hypothesis classes. If the joint pdf in the two classes are correctly estimated, this method guarantees an optimal combining in the minimum Bayes risk sense. Investigating the distribution of confidence features, we found out that the pdfs are well estimated by Gaussian mixture model with full covariance matrix in combining small number of features. In addition, the adaptation of a confidence score by adapting the joint pdf is presented. The proposed methods reduced the classification error rate by 17% from the conventional single feature based confidence scoring method in isolated word Out-of-Vocabulary rejection test.

    Original languageEnglish
    Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    PagesI77-I80
    ISBN (Print)0780388747, 9780780388741
    DOIs
    Publication statusPublished - 2005
    Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
    Duration: 2005 Mar 182005 Mar 23

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    VolumeI
    ISSN (Print)1520-6149

    Other

    Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
    Country/TerritoryUnited States
    CityPhiladelphia, PA
    Period05/3/1805/3/23

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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