# From Disfluency Detection to Intent Detection and Slot Filling

arXiv: https://arxiv.org/abs/2209.08359 · HTML: https://mlsanity.com/paper/2209.08359/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 38 references that are in the map.
- First posted on arXiv 17 Sep 2022.

## Builds on (most cited first, 20 of 20)

- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://mlsanity.com/paper/1606.05250/) (2016)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces](https://mlsanity.com/paper/1805.10190/) (2018)
- [BERT for Joint Intent Classification and Slot Filling](https://mlsanity.com/paper/1902.10909/) (2019)
- [PhoBERT: Pre-trained language models for Vietnamese](https://mlsanity.com/paper/2003.00744/) (2020)
- [Joint Slot Filling and Intent Detection via Capsule Neural Networks](https://mlsanity.com/paper/1812.09471/) (2018)
- [VnCoreNLP: A Vietnamese Natural Language Processing Toolkit](https://mlsanity.com/paper/1801.01331/) (2018)
- [Recent Neural Methods on Slot Filling and Intent Classification for Task-Oriented Dialogue Systems: A Survey](https://mlsanity.com/paper/2011.00564/) (2020)
- [A Pilot Study of Text-to-SQL Semantic Parsing for Vietnamese](https://mlsanity.com/paper/2010.01891/) (2020)
- [Disfluency Detection using a Bidirectional LSTM](https://mlsanity.com/paper/1604.03209/) (2016)
- [Improving Disfluency Detection by Self-Training a Self-Attentive Model](https://mlsanity.com/paper/2004.05323/) (2020)
- [Fluent Translations from Disfluent Speech in End-to-End Speech Translation](https://mlsanity.com/paper/1906.00556/) (2019)
- [A Fast and Accurate Vietnamese Word Segmenter](https://mlsanity.com/paper/1709.06307/) (2017)
- [Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering](https://mlsanity.com/paper/2106.04016/) (2021)
- [Intent Detection and Slot Filling for Vietnamese](https://mlsanity.com/paper/2104.02021/) (2021)
- [COVID-19 Named Entity Recognition for Vietnamese](https://mlsanity.com/paper/2104.03879/) (2021)
- [Disfluency Detection with Unlabeled Data and Small BERT Models](https://mlsanity.com/paper/2104.10769/) (2021)
- [Disfluency Detection using Auto-Correlational Neural Networks](https://mlsanity.com/paper/1808.09092/) (2018)

## Built on by (most cited first, 2 of 2)

- [Streaming Joint Speech Recognition and Disfluency Detection](https://mlsanity.com/paper/2211.08726/) (2022)
- [AgenticASR: Refining Speech Recognition in Real-World Scenarios via an Agentic Approach](https://mlsanity.com/paper/2607.28175/) (2026)

## Abstract (arXiv)

We present the first empirical study investigating the influence of disfluency detection on downstream tasks of intent detection and slot filling. We perform this study for Vietnamese -- a low-resource language that has no previous study as well as no public dataset available for disfluency detection. First, we extend the fluent Vietnamese intent detection and slot filling dataset PhoATIS by manually adding contextual disfluencies and annotating them. Then, we conduct experiments using strong baselines for disfluency detection and joint intent detection and slot filling, which are based on pre-trained language models. We find that: (i) disfluencies produce negative effects on the performances of the downstream intent detection and slot filling tasks, and (ii) in the disfluency context, the pre-trained multilingual language model XLM-R helps produce better intent detection and slot filling performances than the pre-trained monolingual language model PhoBERT, and this is opposite to what generally found in the fluency context.