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---
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language:
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- ar
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pipeline_tag: audio-classification
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library_name: speechbrain
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tags:
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- DIalectID
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- ADI
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- ADI-20
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- speechbrain
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- Identification
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- pytorch
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- embeddings
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datasets:
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- ADI-20
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metrics:
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- f1
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- precision
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- recall
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- accuracy
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---
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## Install Requirements
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### SpeechBrain
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First of all, please install SpeechBrain with the following command:
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```bash
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pip install git+https://github.com/speechbrain/speechbrain.git@develop
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```
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### Clone ADI github repository
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```bash
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git clone https://github.com/elyadata/ADI-20
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cd ADI-20
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pip install -r requirements.txt
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```
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### Perform Arabic Dialect Identification
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```python
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from inference.classifier_attention_pooling import WhisperDialectClassifier
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dialect_id = WhisperDialectClassifier.from_hparams(
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source="",
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hparams_file="hyperparms.yaml",
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savedir="pretrained_DID/tmp").to("cuda")
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dialect_id.device = "cuda"
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dialect_id.classify_file("filenane.wav")
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```
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### Citation
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If using this work, please cite:
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```
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@inproceedings{elleuch2025adi20,
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author = {Haroun Elleuch and Salima Mdhaffar and Yannick Estève and Fethi Bougares},
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title = {ADI‑20: Arabic Dialect Identification Dataset and Models},
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booktitle = {Proceedings of the Annual Conference of the International Speech Communication Association (Interspeech)},
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year = {2025},
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address = {Rotterdam Ahoy Convention Centre, Rotterdam, The Netherlands},
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month = {August},
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days = {17‑21}
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}
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``` |
