Towards large vocabulary Mandarin Chinese speech recognition

Although commercial dictation products are beginning to emerge for English, the existence of a convenient keyboard has prevented pervasive use of dictation. On the other hand, for non alphabetic languages like Chinese, there is no convenient input method. Therefore, dictation may already be a more appealing input method, for Chinese. In this paper, we demonstrate that our sub-syllable HMM recognizer and tone classifier are able to yield state-of-the-art Mandarin Chinese syllable and tone recognition performance (95.7% for syllables and 98.9% for tones). By combining the HMM syllable recognizer and tone classifier, the tonal syllable result (94%) appears adequate for a syllable base dictation machine. Finally, to alleviate the homophone problem of syllable dictation, we developed a high-performance 5,000-word recognition system with 93% accuracy for the correct answer and 99% accuracy for the top 3 candidates