Integrated Processing of Linguistic and Speech Information
Hozumi TANAKA, Takenobu TOKUNAGA and Hui LI
Department of Computer Science, Tokyo Institute of Technology
2-12-1 Ookayama Meguro Tokyo 152 JAPAN
It is obvious that successful speech recognition requires the use of
linguistic information. For this purpose, a generalized LR (GLR)
parser provides an exceptionally competent and flexible framework to
combine linguistic information with phonological information.
The combination of a GLR parser and allophone models is considered very effective for enhancing the recognition accuracy in a large vocabulary continuous speech recognition. The main problem of integrating GLR parsing into an allophone-based recognition system is how to solve the word juncture problem, that is, how to express the phones at a word boundary with allophone models.
This paper proposes a new method called CPM ( Constraint Propagation Method ) to generate an allophone-based LR table, which can effectively solve the word juncture problem. In our method, by introducing the allophone rules into the CFG and lexical rules, an LR table is generated, then the LR table is modified on the basis of an allophone connection matrix by applying the constraint propagation method. With this modified LR table, precise allophone predictions for speech recognition can be obtained.
Keywords: canonical LR table, GLR, allophone, constraints propagation, speech recognition