Transition-Based Disfluency Detection using LSTMs

EMNLP 2017 Shaolei WangWanxiang CheYue ZhangMeishan ZhangTing Liu

In this paper, we model the problem of disfluency detection using a transition-based framework, which incrementally constructs and labels the disfluency chunk of input sentences using a new transition system without syntax information. Compared with sequence labeling methods, it can capture non-local chunk-level features; compared with joint parsing and disfluency detection methods, it is free for noise in syntax... (read more)

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