TY - JOUR
T1 - Language boundary detection and identification of mixed-language speech based on map estimation
AU - Shia, Chi Jiun
AU - Chiu, Yu Hsien
AU - Hsieh, Jia Hsin
AU - Wu, Chung Hsien
PY - 2004/9/28
Y1 - 2004/9/28
N2 - 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.
AB - 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.
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M3 - Conference article
AN - SCOPUS:4544379390
SN - 1520-6149
VL - 1
JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
T2 - Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing
Y2 - 17 May 2004 through 21 May 2004
ER -