A syllable-synchronous network search algorithm for word decoding in Chinese speech recognition

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