Lattice-based continuous Chinese speech indexing based on mutual information confidence measure
基于互信息置信度的网格连续汉语语音检索

Nowadays, with the overwhelming amounts of speech data rushing in our life, higher and higher accuracy of speech indexing techniques is required. This paper mainly studied a converted syllable lattice-based approach in a Chinese continuous speech indexing task. Aiming at the computation of confidence measure in a speech indexing system, this paper proposed a confidence measure method based on mutual information between syllables, which was used in a lattice construction system for speech indexing. The method took full advantage of the context mutual information, which could describe Chinese language model more exactly and logically. The experiment results show that using the proposed method to build a converted syllable lattice in a speech indexing system, the FOM of which has great improvement comparing with posterior probability based method and N-best based method. This best system for Chinese speech indexing achieves a FOM of 83.7%.