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| Paper: | SP-P3.6 |
| Session: | Topics in Speaker and Langauge Recognition |
| Time: | Tuesday, May 18, 15:30 - 17:30 |
| Presentation: |
Poster |
| Topic: |
Speech Processing: Language Identification |
| Title: |
LANGUAGE BOUNDARY DETECTION AND INDENTIFICATION OF MIXED-LANGUAGE SPEECH BASED ON MAP ESTIMATION |
| Authors: |
Chi-Jiun Shia; National Cheng-Kung University | | |
| | Yu-Hsien Chiu; National Cheng-Kung University | | |
| | Jia-Hsin Hsieh; National Cheng-Kung University | | |
| | Chung-Hsien Wu; National Cheng-Kung University | | |
| Abstract: |
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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