Error detection in automatic speech recognition

Seyed Farshid Hosseini Zavareh, Ingrid Zukerman, Su Nam Kim, Thomas Kleinbauer

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    5 Citations (Scopus)

    Abstract

    We offer a supervised machine learning approach for recognizing erroneous words in the output of a speech recognizer. We have investigated several sets of features combined with two word configurations, and compared the performance of two classifiers: Decision Trees and Naïve Bayes. Evaluation was performed on a corpus of 400 spoken referring expressions, with Decision Trees yielding a high recognition accuracy.

    Original languageEnglish
    Title of host publicationAustralasian Language Technology Association Workshop 2013 - Proceedings of the Workshop (ALTA)
    EditorsSarvnaz Karimi, Karin Verspoor
    Place of PublicationStroudsburg PA USA
    PublisherAssociation for Computational Linguistics (ACL)
    Pages101-105
    Number of pages5
    Publication statusPublished - 2013
    EventAustralasian Language Technology Association Workshop 2013 - Queensland University of Technology, Brisbane, Australia
    Duration: 4 Dec 20136 Dec 2013
    Conference number: 11th
    https://www.aclweb.org/anthology/events/alta-2013/ (Proceedings)

    Conference

    ConferenceAustralasian Language Technology Association Workshop 2013
    Abbreviated titleALTAW 2013
    Country/TerritoryAustralia
    CityBrisbane
    Period4/12/136/12/13
    Internet address

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