Tunisian Arabic ASR Model with wav2vec2
This repository provides all the necessary tools to perform automatic speech recognition from an end-to-end system pretrained on Tunisian arabic dialect
Performance
The following table summarizes the performance of the model on various considered test sets :
| Dataset | CER | WER | |-------------- |------- |------- | | TARIC | 6.22 | 10.55 | | IWSLT | 21.18 | 39.53 | | TunSwitch TO | 9.67 | 25.54 |
More details about the test sets, and the conditions leading to this performance in the paper.
Datasets
This ASR model was trained on :
- TARIC : The corpus, named TARIC (Tunisian Arabic Railway Interaction Corpus) has a collection of audio recordings and transcriptions from dialogues in the Tunisian Railway Transport Network. - Taric Corpus -
- IWSLT : A Tunisian conversational speech - IWSLT Corpus-
- TunSwitch : Our crowd-collected dataset described in the paper presented below.
Inference
Install
pip install speechbrain transformers