Context-dependent error correction of spoken referring expressions

Ingrid Zukerman, Andisheh Partovi, Su Nam Kim

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    1 Citation (Scopus)

    Abstract

    We integrate a supervised machine learning mechanism for detecting erroneous words in the output of a speech recognizer with a two-tier error-correction approach that features (1) a noisy-channel model that replaces erroneous words with generic words, and (2) a phonetic-similarity mechanism that refines the generic words based on a short list of candidate interpretations. Our results, obtained on a corpus of 341 referring expressions, show that the first tier improves interpretation performance, and the second tier yields further improvements.
    Original languageEnglish
    Title of host publicationInterspeech 2015: Speech Beyond Speech
    EditorsSebastian Moller, Hermann Ney, Bernd Mobius, Elmar Noth, Stefan Steidl
    Place of PublicationBaixas France
    PublisherInternational Speech Communication Association (ISCA)
    Pages2032 - 2036
    Number of pages5
    Publication statusPublished - 2015
    EventAnnual Conference of the International Speech Communication Association (was Eurospeech) 2015 - Dresden, Germany
    Duration: 6 Sep 201510 Sep 2015
    Conference number: 16th
    http://interspeech2015.org/

    Conference

    ConferenceAnnual Conference of the International Speech Communication Association (was Eurospeech) 2015
    Abbreviated titleInterspeech 2015
    CountryGermany
    CityDresden
    Period6/09/1510/09/15
    Internet address

    Cite this

    Zukerman, I., Partovi, A., & Kim, S. N. (2015). Context-dependent error correction of spoken referring expressions. In S. Moller, H. Ney, B. Mobius, E. Noth, & S. Steidl (Eds.), Interspeech 2015: Speech Beyond Speech (pp. 2032 - 2036). International Speech Communication Association (ISCA).