An initial study on a segmental probability model approach to large-vocabulary continuous Mandarin speech recognition
Resource
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Journal
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Journal Volume
2
Pages
II133 - II136
Date Issued
1994-04
Date
1994-04
Author(s)
DOI
N/A
Abstract
This paper presents an initial study to perform Iarge-vocabuIary continuous Mandarin speech recognition based on a Segmental Probability Model(SPM) approach. SPM was first proposed for recognition of isolated Mandarin syllables, in which every syllable must be equally segmented before recognition. Therefore, A concatenated syllable matching algorithm in place of the conventional Viterbi search algorithm is therefore introduced t o perform the recognition process based on SPM. In addition, a training procedure is also proposed to reestimate the SPM parameters for continuous speech. Preliminary simulation results indicate that significant improvements in both recognition rates and speed can be achieved as compared to the conventional HMM-based Viterbi search approaches. © 1994 IEEE
Event(s)
Proceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing. Part 2 (of 6)
SDGs
Other Subjects
Signal processing; Viterbi algorithm; Continuous speech; Mandarin speech recognition; Mandarin syllable; Matching algorithm; Recognition process; Segmental probability model; Training procedures; Viterbi search algorithms; Speech recognition
Type
conference paper
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