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---
library_name: transformers
tags:
- audio
- automatic-speech-recognition
license: mit
language:
- ar
---
# ArTST (ASR task)
ArTST model finetuned for automatic speech recognition (speech-to-text) on MGB2.
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** Speech Lab, MBZUAI
- **Model type:** SpeechT5
- **Language:** Arabic
- **Finetuned from:** (ArTST pretrained)[https://github.com/mbzuai-nlp/ArTST]
## How to Get Started with the Model
```python
import soundfile as sf
from transformers import (
SpeechT5Config,
SpeechT5FeatureExtractor,
SpeechT5ForSpeechToText,
SpeechT5Processor,
SpeechT5Tokenizer,
)
from custom_tokenizer import CustomTextTokenizer
device = "cuda" if torch.cuda.is_available() else "cpu"
tokenizer = SpeechT5Tokenizer.from_pretrained("mbzuai/artst_asr")
processor = SpeechT5Processor.from_pretrained("mbzuai/artst_asr" , tokenizer=tokenizer)
model = SpeechT5ForSpeechToText.from_pretrained("mbzuai/artst_asr").to(device)
audio, sr = sf.read("audio.wav")
inputs = processor(audio=audio, sampling_rate=sr, return_tensors="pt")
predicted_ids = model.generate(**inputs.to(device), max_length=150)
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
print(transcription[0])
```
### Model Sources [optional]
- **Repository:** [github](https://github.com/mbzuai-nlp/ArTST)
- **Paper :** [ArabicNLP2023](https://aclanthology.org/2023.arabicnlp-1.5/)
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## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
```
@inproceedings{toyin-etal-2023-artst,
title = "{A}r{TST}: {A}rabic Text and Speech Transformer",
author = "Toyin, Hawau and
Djanibekov, Amirbek and
Kulkarni, Ajinkya and
Aldarmaki, Hanan",
booktitle = "Proceedings of ArabicNLP 2023",
month = dec,
year = "2023",
address = "Singapore (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.arabicnlp-1.5",
doi = "10.18653/v1/2023.arabicnlp-1.5",
pages = "41--51",
}
```
<!-- **APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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