---
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: tun_transcription
    dtype: string
  - name: tun_slu_annoation
    dtype: string
  - name: eng_slu_annotation
    dtype: string
  splits:
  - name: train
    num_bytes: 322907160.421
    num_examples: 2677
  - name: validation
    num_bytes: 84983675.0
    num_examples: 595
  - name: test
    num_bytes: 121863417.0
    num_examples: 893
  download_size: 335804926
  dataset_size: 529754252.421
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---


# SLURP-TN : Resource for Tunisian Dialect Spoken Language Understanding


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Contact person : fethi.bougares@elyadata.com 

Spoken Language Understanding (SLU) aims to extract the semantic information from the speech utterance of user
queries. It is a core component in a task-oriented dialogue system. With the spectacular progress of deep neural
network models and the evolution of pre-trained language models, SLU has obtained significant breakthroughs.
However, only a few high-resource languages have taken advantage of this progress due to the absence of SLU
resources. In this paper, we seek to mitigate this obstacle by introducing SLURP-TN. This dataset was created by
recording 55 native speakers uttering sentences in Tunisian dialect, manually translated from six SLURP domains.
The result is an SLU Tunisian dialect dataset that comprises 4165 sentences recorded into around 5 hours of acoustic
material. We also develop a number of Automatic Speech Recognition and SLU models exploiting SLUTP-TN.


## Paper 
 https://arxiv.org/pdf/2603.21940

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->


- **Curated by:**  Haroun Elleuch
- **Shared by [optional]:** Fethi Bougares
- **Language(s) (NLP)** : Tunisian Arabic 
- **License:** CC BY-NC-ND 4.0 license

Enjoy using this data set for research-only activities and don't forget to cite the related paper :) 
Below the bibtext entry if you use this data set  :


**BibTeX:**
```
@inproceedings{slurptn,
    title = "{SLURP-TN} : {R}esource for {T}unisian {D}ialect {S}poken {L}anguage {U}nderstanding",
    author = "Haroun Elleuch and Salima Mdhaffar and Yannick Estève and Fethi Bougares",
    booktitle = "LREC",
    month = mai,
    year = "2026",
    address = "Mallorca, Spain"
}
```