Native speakers of Mandarin produce and perceive tones in ways that depend on the focus with which each word is produced . This paper gives one approach to improving tone recognition algorithms using focus, by training different support vector machines on syllables conditional on their position with respect to the focused word in a sentence. In a four-way tone classification task on focus-labelled laboratory Mandarin speech data collected by Xu , error rates improve from 15.2% without using focus to 8.7 % when using focus. Using the fact that tones on syllables in focused words are especially easy to recognize, we propose a tone recognition algorithm that makes use of focus without requiring focus labels in either training or test set. The algorithm has an error rate of 9.8 % on this data set
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