This paper presents a new context dependent tone recognition method. First we suggest that there be more than five tone modes in Chinese continuous speech. We get all new tone modes by grouping all tone feature vectors to a specific number of categories. Secondly, we recognize a sentence with the new tone modes and get the new tone sequence. Finally, we find out each original tone of the sentence which has the maximum a posteriori probability for the corresponding new tone and its context new tones. In a ten-person test set, which includes about 20,000 tones, we achieve a higher average recognition rate with the MAP-based context dependent tone method than that with the conventional context dependent tone method.
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