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--- |
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license: mit |
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tags: |
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- asr |
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- whisper |
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- speech-recognition |
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--- |
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```python |
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from transformers import WhisperProcessor, WhisperForConditionalGeneration |
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import librosa |
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import torch |
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model_name = "basharalrfooh/whisper-samll-quran" |
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processor = WhisperProcessor.from_pretrained(model_name) |
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model = WhisperForConditionalGeneration.from_pretrained(model_name) |
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model.config.forced_decoder_ids = None |
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audio_file = "Your .wav file" |
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speech_array, sampling_rate = librosa.load(audio_file, sr=16000) |
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inputs = processor(speech_array, return_tensors="pt", sampling_rate=sampling_rate) |
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with torch.no_grad(): |
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predicted_ids = model.generate(inputs["input_features"]) |
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# Decode token IDs to text |
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transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True) |
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print(f"Transcription: {transcription}") |
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