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TuniSpeech-AI/
whisper-tunisian-dialect

Name: whisper-tunisian-dialect
Availability: InStock

safetensors

whisper

cc-by-nc-4.0

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Whisper Tunisian Dialect ASR (TuniSpeech‑21h)

Whisper Tunisian Dialect ASR

Overview

Whisper Tunisian Dialect ASR is a fine-tuned speech recognition model based on OpenAI Whisper-large-v2, adapted to the Tunisian Arabic dialect using the TuniSpeech corpus (~21 hours).

The model is designed for:

Automatic Speech Recognition (ASR) in Tunisian dialect
Transcription of short spontaneous speech
Research on low-resource Arabic dialects

Repository:
https://huggingface.co/TuniSpeech-AI/whisper-tunisian-dialect

Model Architecture

Base model: Whisper-large-v2
Fine-tuning strategy: LoRA → merged into full model weights
Framework: Hugging Face Transformers
Decoding:
- Forced language: Arabic (ar)
- Task: transcription (not translation)

After training, LoRA adapters were fully merged, producing a standalone Whisper checkpoint compatible with standard inference pipelines.

Training Data

TuniSpeech Corpus

Language: Tunisian Arabic dialect
Duration: ~21 hours
Recording conditions:
- Real speech\
- Spontaneous pronunciation\
- Speaker variability

The dataset targets dialectal phonetics and vocabulary, which are poorly covered by standard Arabic ASR systems.

Experimental Setup

Input audio:
- Resampled to 16 kHz mono
Training method:
- Parameter-efficient fine-tuning (LoRA)
- Followed by weight merging

Evaluation focused on:

Dialectal word recognition
Short utterance transcription
Real-world speech robustness

Usage

Installation

pip install torch transformers librosa gradio

Python Inference

python

from transformers import pipeline

pipe = pipeline(
    "automatic-speech-recognition",
    model="TuniSpeech-AI/whisper-tunisian-dialect"
)

result = pipe("audio.wav")
print(result["text"])

Hugging Face Space

An interactive demo is available:

Upload or record Tunisian speech → get transcription instantly.

⚠️ On CPU, processing is slow.
Recommended:

Use short audio (< 5 s)

Citation

If you use this model, please cite the associated work on:

Whisper fine-tuning for Tunisian dialect speech recognition using the TuniSpeech-21H corpus.

bibtex

@inproceedings{tunispeech_whisper_2026,
  title     = {A New Tunisian Arabic Corpus and Benchmark for Automatic Speech Recognition},
  author    = {Sghaier, Mohamed Ali and Bellagha, Mohamed Lazhar and Zrigui, Mounir},
  booktitle = {In Proceedings of the 18th International Conference on Agents and Artificial Intelligence},
  year      = {2026}
}