Duplicate from ras0k/WhisperX-v2

Co-authored-by: 0 <ras0k@users.noreply.huggingface.co>

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README.md

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+---
+title: WhisperX V2
+emoji: 🌖
+colorFrom: purple
+colorTo: indigo
+sdk: gradio
+sdk_version: 3.24.1
+app_file: app.py
+pinned: false
+license: bsd
+duplicated_from: ras0k/WhisperX-v2
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import whisperx
+import whisper
+
+def transcribe(audio_file):
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+
+    # Transcribe with original Whisper
+    model = whisper.load_model("large", device)
+    result = model.transcribe(audio_file)
+
+    # Load alignment model and metadata
+    model_a, metadata = whisperx.load_align_model(language_code=result["language"], device=device)
+
+    # Align Whisper output
+    result_aligned = whisperx.align(result["segments"], model_a, metadata, audio_file, device)
+
+    return {"aligned": result_aligned["segments"], "word_segments": result_aligned["word_segments"]}
+
+inputs = gr.inputs.Audio(source="upload", type="filepath")
+outputs = gr.outputs.JSON()
+
+gr.Interface(fn=transcribe, inputs=inputs, outputs=outputs).launch()

requirements.txt

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+gradio
+git+https://github.com/m-bain/whisperx.git