An N-gram based Chinese syllable evaluation approach for speech recognition error detection

In order to find errors and correct words after Chinese speech recognition to improve its accuracy rate, an N-gram based phonetic syllable evaluation approach is proposed according to the conjunction rules in Chinese syllables. In this paper, Bigram and Trigram model are used with two kinds of smoothing methods for comparison. Evaluation results show that it can achieve a precision rate up to 72.44% for error detection, which can provide more reliable target for error correction.