# Robust cross-domain disfluency detection with pattern match networks

arXiv: https://arxiv.org/abs/1811.07236 · HTML: https://mlsanity.com/paper/1811.07236/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Nov 2018.

## Built on by (most cited first, 1 of 1)

- [Disfluency Detection with Unlabeled Data and Small BERT Models](https://mlsanity.com/paper/2104.10769/) (2021)

## Abstract (arXiv)

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.