MBZUAI
/

artst_asr_v3_qasr

@@ -1,199 +1,114 @@
 ---
 library_name: transformers
-tags: []
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 ---
 library_name: transformers
+tags:
+- asr
+license: mit
+language:
+- ar
+pipeline_tag: automatic-speech-recognition
 ---
+# ArTST-v3 (ASR task)
+ArTST model finetuned for  automatic speech recognition (speech-to-text) on QASR (best for Dialectal Arabic Variants)
 ### Model Description
+- **Developed by:** Speech Lab, MBZUAI
+- **Model type:** SpeechT5
+- **Language:** Arabic
 ## How to Get Started with the Model
+```python
+import soundfile as sf
+from transformers import (
+    SpeechT5Config,
+    SpeechT5FeatureExtractor,
+    SpeechT5ForSpeechToText,
+    SpeechT5Processor,
+    SpeechT5Tokenizer,
+)
+device = "cuda" if torch.cuda.is_available() else "CPU"
+model_id="mbzuai/artst_asr_v3_qasr"
+tokenizer = SpeechT5Tokenizer.from_pretrained(model_id)
+processor = SpeechT5Processor.from_pretrained(model_id , tokenizer=tokenizer)
+model = SpeechT5ForSpeechToText.from_pretrained(model_id).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, num_beams=10)
+transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
+print(transcription[0])
+```
+or using pipeline
+```python
+import librosa
+from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor
+model_id="mbzuai/artst_asr_v3"
+processor = AutoProcessor.from_pretrained(model_id)
+model = AutoModelForSpeechSeq2Seq.from_pretrained(model_id).to(device)
+pipe = pipeline(
+    "automatic-speech-recognition",
+    model=model,
+    tokenizer=processor.tokenizer,
+    feature_extractor=processor.feature_extractor,
+    torch_dtype=torch_dtype,
+    device=device,
+)
+wav, sr = librosa.load("audio.wav", sr=16000)
+pipe(wav, generate_kwargs={'num_beams': 10, 'early_stopping': True})['text']
+```
+### Model Sources [optional]
+- **Repository:** [github](https://github.com/mbzuai-nlp/ArTST)
+- **Paper :** [ArXiv](https://arxiv.org/pdf/2411.05872)
+<!-- - **Demo [optional]:** [More Information Needed] -->
+## Citation
 **BibTeX:**
+```
+@misc{djanibekov2024dialectalcoveragegeneralizationarabic,
+      title={Dialectal Coverage And Generalization in Arabic Speech Recognition},
+      author={Amirbek Djanibekov and Hawau Olamide Toyin and Raghad Alshalan and Abdullah Alitr and Hanan Aldarmaki},
+      year={2024},
+      eprint={2411.05872},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2411.05872},
+}
+@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",
+}
+```