Title :
A syllable-synchronous network search algorithm for word decoding in Chinese speech recognition
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Abstract :
The Chinese language is syllabic in nature with frequent homonym phenomena and severe word boundary uncertainty problem. This makes the Chinese continuous speech recognition (CSR) slightly difficult. In order to solve these problems, a Chinese syllable-synchronous network search (SSNS) algorithm is proposed. Together with the vocabulary word search tree and the N-gram based language model, the syllable-synchronous network search algorithm gives a good solution to the Chinese syllable-to-word conversion. In addition, this algorithm is a good method for the accent Chinese speech recognition. The experimental results have showed that the SSNS algorithm can achieve a good overall continuous Chinese speech recognition system performance
Keywords :
decoding; grammars; natural languages; speech recognition; tree searching; Chinese speech recognition; Chinese syllable-to-word conversion; N-gram based language model; accent Chinese speech recognition; continuous speech recognition; experimental results; homonym phenomena; syllable-synchronous network search algorithm; system performance; vocabulary word search tree; word boundary uncertainty problem; word decoding; Bayesian methods; Carbon capture and storage; Cascading style sheets; Decoding; Equations; Intelligent networks; Laboratories; Natural languages; Speech recognition; Viterbi algorithm;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.759738
