Acoustic-Phonetic Unit Similarities For Context Dependent Acoustic Model Portability

This paper addresses particularly the use of acoustic-phonetic unit similarities for portability of context dependent acoustic models to new languages. Since the IPA-based method is limited to a source/target phoneme mapping table construction, an estimation method of the similarity between two phonemes is proposed in this paper. Based on these phoneme similarities, some estimation methods for polyphone similarity and clustered polyphonic model similarity are investigated. For a new language, first a polyphonic decision tree is built with a small amount of speech data. Then, clustered models in the target language are duplicated from the nearest clustered models in the source language and adapted with limited data to the target language. Results obtained from the experiments demonstrate the feasibility of these methods

[1]  Joachim Köhler,et al.  Multi-lingual phoneme recognition exploiting acoustic-phonetic similarities of sounds , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[2]  Chafic Mokbel,et al.  Towards multilingual speech recognition using data driven source/target acoustical units association , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[3]  Elizabeth C. Botha,et al.  An acoustic distance measure for automatic cross-language phoneme mapping , 2001 .

[4]  Laurent Besacier,et al.  First steps in fast acoustic modeling for a new target language: application to Vietnamese , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[5]  Tanja Schultz,et al.  Language-independent and language-adaptive acoustic modeling for speech recognition , 2001, Speech Commun..

[6]  Jean-François Serignat,et al.  Spoken and Written Language Resources for Vietnamese , 2004, LREC.

[7]  Klaus Ries,et al.  The Karlsruhe-Verbmobil speech recognition engine , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[8]  Andrej Zgank,et al.  Agglomerative vs. tree-based clustering for the definition of multilingual set of triphones , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[9]  Andreas Stolcke,et al.  SRILM - an extensible language modeling toolkit , 2002, INTERSPEECH.

[10]  J. Kohler.  Multi-lingual phoneme recognition exploiting acoustic-phonetic similarities of sounds , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[11]  William J. Byrne,et al.  Towards language independent acoustic modeling , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).