# Intent Recognition and Unsupervised Slot Identification for Low Resourced Spoken Dialog Systems

arXiv: https://arxiv.org/abs/2104.01287 · HTML: https://mlsanity.com/paper/2104.01287/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 31 references that are in the map.
- First posted on arXiv 3 Apr 2021.

## Builds on (most cited first, 16 of 16)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Deep Speech: Scaling up end-to-end speech recognition](https://mlsanity.com/paper/1412.5567/) (2014)
- [Speech Model Pre-training for End-to-End Spoken Language Understanding](https://mlsanity.com/paper/1904.03670/) (2019)
- [Towards end-to-end spoken language understanding](https://mlsanity.com/paper/1802.08395/) (2018)
- [Universal Phone Recognition with a Multilingual Allophone System](https://mlsanity.com/paper/2002.11800/) (2020)
- [THCHS-30 : A Free Chinese Speech Corpus](https://mlsanity.com/paper/1512.01882/) (2015)
- [End-to-End Neural Transformer Based Spoken Language Understanding](https://mlsanity.com/paper/2008.10984/) (2020)
- [Spoken Language Understanding on the Edge](https://mlsanity.com/paper/1810.12735/) (2018)
- [Capsule Networks for Low Resource Spoken Language Understanding](https://mlsanity.com/paper/1805.02922/) (2018)
- [HarperValleyBank: A Domain-Specific Spoken Dialog Corpus](https://mlsanity.com/paper/2010.13929/) (2020)
- [Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages](https://mlsanity.com/paper/2011.03646/) (2020)
- [Mere account mein kitna balance hai? -- On building voice enabled Banking Services for Multilingual Communities](https://mlsanity.com/paper/2010.16411/) (2020)

## Built on by (most cited first, 4 of 4)

- [On Building Spoken Language Understanding Systems for Low Resourced Languages](https://mlsanity.com/paper/2205.12818/) (2022)
- [Decoding Emotions: A comprehensive Multilingual Study of Speech Models for Speech Emotion Recognition](https://mlsanity.com/paper/2308.08713/) (2023)
- [Intent Classification Using Pre-trained Language Agnostic Embeddings For Low Resource Languages](https://mlsanity.com/paper/2110.09264/) (2021)
- [Creating Spoken Dialog Systems in Ultra-Low Resourced Settings](https://mlsanity.com/paper/2312.06266/) (2023)

## Abstract (arXiv)

Intent Recognition and Slot Identification are crucial components in spoken language understanding (SLU) systems. In this paper, we present a novel approach towards both these tasks in the context of low resourced and unwritten languages. We present an acoustic based SLU system that converts speech to its phonetic transcription using a universal phone recognition system. We build a word-free natural language understanding module that does intent recognition and slot identification from these phonetic transcription. Our proposed SLU system performs competitively for resource rich scenarios and significantly outperforms existing approaches as the amount of available data reduces. We observe more than 10% improvement for intent classification in Tamil and more than 5% improvement for intent classification in Sinhala. We also present a novel approach towards unsupervised slot identification using normalized attention scores. This approach can be used for unsupervised slot labelling, data augmentation and to generate data for a new slot in a one-shot way with only one speech recording