Title :
Isolated Mandarin base-syllable recognition based upon the segmental probability model
Author :
Lyu, Ren-Yuan ; Hong, I-Chung ; Shen, Jia-Lin ; Lee, Ming-Yu ; Lee, Lin-shan
Author_Institution :
Dept. of Electr. Eng., Chang Gung Univ., Taoyuan, Taiwan
fDate :
5/1/1998 12:00:00 AM
Abstract :
A segmental probability model (SPM) is proposed for fast and accurate recognition of the highly confusing isolated Mandarin base-syllables by deleting the state transition probabilities of continuous density hidden Markov models (CHMM), abandoning the dynamic programming process, letting the states equally segment the base-syllables deterministically, and using several special approaches to improve the accuracy and speed. This is achieved by considering the special characteristics of the target vocabulary
Keywords :
hidden Markov models; natural languages; probability; speech processing; speech recognition; CHMM; accurate recognition; continuous density hidden Markov models; fast recognition; isolated Mandarin base-syllable recognition; segmental probability model; state transition probabilities; vocabulary; Councils; Decoding; Dynamic programming; Helium; Hidden Markov models; Information science; Scanning probe microscopy; Speech recognition; Training data; Vocabulary;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
