Language boundary detection and identification of mixed-language speech based on map estimation

Chi Jiun Shia, Yu Hsien Chiu, Jia Hsin Hsieh, Chung Hsien Wu

研究成果: Conference article同行評審

17 引文 斯高帕斯(Scopus)


This paper proposes a Maximum a Posteriori (MAP) based approach to jointly segment and identify an utterance with mixed languages. A statistical framework for language boundary detection and language identification is proposed. First, the MAP estimation is used to determine the boundary number and positions. Further, an LSA-based GMM and a VQ-based bi-gram language model are proposed to characterize a language and used for language identification. Finally, a likelihood ratio test approach is used to determine the optimal number of language boundaries. Experimental results show that the proposed approach exhibits encouraging potential in mixed-language segmentation and identification.

期刊ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
出版狀態Published - 2004 9月 28
事件Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
持續時間: 2004 5月 172004 5月 21

All Science Journal Classification (ASJC) codes

  • 軟體
  • 訊號處理
  • 電氣與電子工程