Speaker's intention prediction modules can be widely used as a pre-processor for reducing the search space of an automatic speech recognizer. They also can be used as a preprocessor for generating a proper sentence in a dialogue system. We propose a statistical model to predict speakers' intentions by using multi-level features. Using the multi-level features (morpheme-level features, discourse-level features, and domain knowledge-level features), the proposed model predicts speakers' intentions that may be implicated in next utterances. In the experiments, the proposed model showed better performances (about 29% higher accuracies) than the previous model. Based on the experiments, we found that the proposed multi-level features are very effective in speaker's intention prediction.
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