Instructions to use NightPrince/Nemo-Arabic-STT-Diacritized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use NightPrince/Nemo-Arabic-STT-Diacritized with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("NightPrince/Nemo-Arabic-STT-Diacritized") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Add DiacritizedASR one-call pipeline wrapper
Browse files- pipeline.py +36 -0
pipeline.py
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"""One-call Arabic speech-to-text with forced diacritization (tashkeel).
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Wraps the NeMo ASR model and the CATT diacritizer as a single object so
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transcription -> diacritization happens as one process, one call.
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"""
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from __future__ import annotations
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import nemo.collections.asr as nemo_asr
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from diacritize import Diacritizer
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class DiacritizedASR:
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"""Arabic speech-to-text that returns fully diacritized transcripts."""
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def __init__(
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self,
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nemo_path: str = "stt_ar_fastconformer_hybrid_large_pcd_v1.0.nemo",
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catt_ckpt: str = "best_ed_mlm_ns_epoch_178.pt",
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device: str | None = None,
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) -> None:
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self.asr_model = nemo_asr.models.EncDecHybridRNNTCTCBPEModel.restore_from(nemo_path)
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self.asr_model.eval()
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self.diacritizer = Diacritizer(ckpt=catt_ckpt, device=device)
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def transcribe(self, audio_path: str) -> str:
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"""Audio file path -> diacritized Arabic text."""
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plain = self.asr_model.transcribe([audio_path])[0].text
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return self.diacritizer.diacritize_texts([plain])[0]
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if __name__ == "__main__":
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import sys
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model = DiacritizedASR()
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print(model.transcribe(sys.argv[1]))
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