A Neural Attention Model for Disfluency Detection

COLING 2016 Shaolei WangWanxiang CheTing Liu

In this paper, we study the problem of disfluency detection using the encoder-decoder framework. We treat disfluency detection as a sequence-to-sequence problem and propose a neural attention-based model which can efficiently model the long-range dependencies between words and make the resulting sentence more likely to be grammatically correct... (read more)

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