| 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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