Robust cross-domain disfluency detection with pattern match networks

Vicky Zayats; Mari Ostendorf

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arXiv · 1811.07236

Robust cross-domain disfluency detection with pattern match networks

Vicky Zayats·Mari Ostendorf

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Abstract

In this paper we introduce a novel pattern match neural network architecture that uses neighbor similarity scores as features, eliminating the need for feature engineering in a disfluency detection task. We evaluate the approach in disfluency detection for four different speech genres, showing that the approach is as effective as hand-engineered pattern match features when used on in-domain data and achieves superior performance in cross-domain scenarios.

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Vicky Zayats, Mari Ostendorf. 2018-11-17. Robust cross-domain disfluency detection with pattern match networks. https://arxiv.org/abs/1811.07236

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