# A Persian Benchmark for Joint Intent Detection and Slot Filling

arXiv: https://arxiv.org/abs/2303.00408 · HTML: https://mlsanity.com/paper/2303.00408/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 30 references that are in the map.
- First posted on arXiv 1 Mar 2023.

## Builds on (most cited first, 15 of 15)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [AraBERT: Transformer-based Model for Arabic Language Understanding](https://mlsanity.com/paper/2003.00104/) (2020)
- [Multilingual Translation with Extensible Multilingual Pretraining and Finetuning](https://mlsanity.com/paper/2008.00401/) (2020)
- [BERT for Joint Intent Classification and Slot Filling](https://mlsanity.com/paper/1902.10909/) (2019)
- [Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling](https://mlsanity.com/paper/1609.01454/) (2016)
- [A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling](https://mlsanity.com/paper/1907.00390/) (2019)
- [End-to-End Slot Alignment and Recognition for Cross-Lingual NLU](https://mlsanity.com/paper/2004.14353/) (2020)
- [A Co-Interactive Transformer for Joint Slot Filling and Intent Detection](https://mlsanity.com/paper/2010.03880/) (2020)
- [A Survey on Spoken Language Understanding: Recent Advances and New Frontiers](https://mlsanity.com/paper/2103.03095/) (2021)
- [Hierarchically-Refined Label Attention Network for Sequence Labeling](https://mlsanity.com/paper/1908.08676/) (2019)
- [Intent Detection and Slot Filling for Vietnamese](https://mlsanity.com/paper/2104.02021/) (2021)
- [PQuAD: A Persian Question Answering Dataset](https://mlsanity.com/paper/2202.06219/) (2022)
- [Prior Knowledge Driven Label Embedding for Slot Filling in Natural Language Understanding](https://mlsanity.com/paper/2003.09831/) (2020)
- [DeepSentiPers: Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus](https://mlsanity.com/paper/2004.05328/) (2020)
- [PeCoQ: A Dataset for Persian Complex Question Answering over Knowledge Graph](https://mlsanity.com/paper/2106.14167/) (2021)

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

- [Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti](https://mlsanity.com/paper/2310.10935/) (2023)
- [A Hybrid Architecture for Out of Domain Intent Detection and Intent Discovery](https://mlsanity.com/paper/2303.04134/) (2023)

## Abstract (arXiv)

Natural Language Understanding (NLU) is important in today's technology as it enables machines to comprehend and process human language, leading to improved human-computer interactions and advancements in fields such as virtual assistants, chatbots, and language-based AI systems. This paper highlights the significance of advancing the field of NLU for low-resource languages. With intent detection and slot filling being crucial tasks in NLU, the widely used datasets ATIS and SNIPS have been utilized in the past. However, these datasets only cater to the English language and do not support other languages. In this work, we aim to address this gap by creating a Persian benchmark for joint intent detection and slot filling based on the ATIS dataset. To evaluate the effectiveness of our benchmark, we employ state-of-the-art methods for intent detection and slot filling.