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 - 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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