標題: A STUDY ON CROSS-LANGUAGE KNOWLEDGE INTEGRATION IN MANDARIN LVCSR
作者: Chiang, Chen-Yu
Siniscalchi, Sabato Marco
Wang, Yih-Ru
Chen, Sin-Horng
Lee, Chin-Hui
電機工程學系
Department of Electrical and Computer Engineering
關鍵字: LVCSR;prosody modeling;attribute detector;knowledge integration
公開日期: 2012
摘要: We present a cross-language knowledge integration framework to improve the performance in large vocabulary continuous speech recognition. Two types of knowledge sources, manner attribute and prosodic structure, are incorporated. For manner of articulation, cross-lingual attribute detectors trained with an American English corpus (WSJ0) are utilized to verify and rescore hypothesized Mandarin syllables in word lattices obtained with state-of-the-art systems. For the prosodic structure, models trained with an unsupervised joint prosody labeling and modeling technique using a Mandarin corpus (TCC300) are used in lattice rescoring. Experimental results on Mandarin syllable, character and word recognition with the TCC300 corpus show that the proposed approach significantly outperforms the baseline system that does not use articulatory and prosodic information. It also demonstrates a potential of utilizing results from cross-lingual attribute detectors as a language-universal frontend for automatic speech recognition.
URI: http://hdl.handle.net/11536/21522
ISBN: 978-1-4673-2507-3
期刊: 2012 8TH INTERNATIONAL SYMPOSIUM ON CHINESE SPOKEN LANGUAGE PROCESSING
起始頁: 315
結束頁: 319
Appears in Collections:Conferences Paper