Xiaolong Li, Li Deng, Dong Yu, and Alex Acero
19 September 2006
A novel time-synchronous decoder, designed specifically for a Hidden Trajectory Model (HTM) whose likelihood score computation depends on long-span phonetic contexts, is presented. HTM is a recently developed acoustic model aimed to capture the underlying dynamic structure of speech coarticulation and reduction using a compact set of parameters. The long-span nature of the HTM had posed a great technical challenge for developing efficient search algorithms for full evaluation of the model. Taking on the challenge, the decoding algorithm is developed to deal effectively with the exponentially increased search space by HTM-specific techniques for hypothesis representation, word-ending recombination, and hypothesis pruning. Experimental results obtained on the TIMIT phonetic recognition task are reported, extending our earlier HTM evaluation paradigms based on N-best and A* lattice rescoring.
In Proceedings of International Conference on Speech Communication (InterSpeech), 2006
Publisher International Speech Communication Association
© 2007 ISCA. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the ISCA and/or the author.