A study on Hakka and mixed Hakka-Mandarin speech recognition

Tsai Lu Tsai*, Chen Yu Chiang, Hsiu Min Yu, Lieh-Shih Lo, Yih-Ru Wang, Sin-Horng Chen

*Corresponding author for this work

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

    5 Scopus citations

    Abstract

    A first study on Hakka and mixed Hakka-Mandarin speech recognition (SR) is reported in this paper. The main focus of the study is on solving the problem of the lack of a large text corpus for training a reliable language model. In the Hakka SR, several methods to use the information of part of speech and Hakka-Chinese word translation to assist in language modeling are proposed. For mixed language SR, a method to train a mixed Hakka-Mandarin acoustic model is suggested. Experimental results show that the proposed language and acoustic modeling approaches are promising for Hakka and mixed Hakka-Mandarin SR.

    Original languageEnglish
    Title of host publication2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010 - Proceedings
    Pages199-204
    Number of pages6
    DOIs
    StatePublished - 1 Dec 2010
    Event2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010 - Tainan, Taiwan
    Duration: 29 Nov 20103 Dec 2010

    Publication series

    Name2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010 - Proceedings

    Conference

    Conference2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010
    Country/TerritoryTaiwan
    CityTainan
    Period29/11/103/12/10

    Keywords

    • Acoustic model
    • Hakka
    • Language model
    • Mandarin
    • Speech recognition

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