Sajidahamed commited on
Commit
e6d3380
·
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1 Parent(s): e2faa92

Update app.py

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Files changed (1) hide show
  1. app.py +13 -13
app.py CHANGED
@@ -3,38 +3,38 @@ import os
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  import torchaudio
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  from speechbrain.pretrained import EncoderClassifier
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- def accent_detect(video_file):
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- # Save uploaded video
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- if isinstance(video_file, tuple):
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- video_path = video_file[0]
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- else:
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- video_path = "uploaded_input.mp4"
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- with open(video_path, "wb") as f:
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- f.write(video_file.read())
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- # Extract audio
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- os.system(f"ffmpeg -y -i {video_path} -ar 16000 -ac 1 -vn audio.wav")
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  if not os.path.exists("audio.wav") or os.path.getsize("audio.wav") < 1000:
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  return "Audio extraction failed. Please check your file."
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- # Classify accent
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  accent_model = EncoderClassifier.from_hparams(
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  source="speechbrain/lang-id-commonlanguage_ecapa",
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  savedir="tmp_accent_model"
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  )
 
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  signal, fs = torchaudio.load("audio.wav")
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  if signal.shape[0] > 1:
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  signal = signal[0].unsqueeze(0)
 
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  prediction = accent_model.classify_batch(signal)
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  pred_label = prediction[3][0]
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  pred_scores = prediction[1][0]
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  confidence = float(pred_scores.max()) * 100
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- explanation = f"Predicted Accent: {pred_label} ({confidence:.1f}%)\nThe model is {confidence:.0f}% confident this is a {pred_label} English accent."
 
 
 
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  return explanation
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  demo = gr.Interface(
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  fn=accent_detect,
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- inputs=gr.Video(type="filepath", label="Upload a Video File (MP4, WEBM, etc.)"),
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  outputs="text",
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  title="🗣️ English Accent Classifier (Gradio Demo)",
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  description="Upload a short video clip of English speech. This tool predicts the English accent and confidence."
 
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  import torchaudio
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  from speechbrain.pretrained import EncoderClassifier
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+ def accent_detect(video_path):
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+ # video_path is a string file path provided by Gradio
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+ # Extract audio from the video using ffmpeg
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+ os.system(f"ffmpeg -y -i '{video_path}' -ar 16000 -ac 1 -vn audio.wav")
 
 
 
 
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+ # Check if audio.wav was created and is of reasonable size
 
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  if not os.path.exists("audio.wav") or os.path.getsize("audio.wav") < 1000:
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  return "Audio extraction failed. Please check your file."
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+ # Load the accent classification model
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  accent_model = EncoderClassifier.from_hparams(
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  source="speechbrain/lang-id-commonlanguage_ecapa",
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  savedir="tmp_accent_model"
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  )
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+ # Load audio
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  signal, fs = torchaudio.load("audio.wav")
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  if signal.shape[0] > 1:
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  signal = signal[0].unsqueeze(0)
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+ # Predict accent
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  prediction = accent_model.classify_batch(signal)
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  pred_label = prediction[3][0]
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  pred_scores = prediction[1][0]
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  confidence = float(pred_scores.max()) * 100
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+ explanation = (
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+ f"Predicted Accent: {pred_label} ({confidence:.1f}%)\n"
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+ f"The model is {confidence:.0f}% confident this is a {pred_label} English accent."
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+ )
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  return explanation
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  demo = gr.Interface(
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  fn=accent_detect,
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+ inputs=gr.Video(label="Upload a Video File (MP4, WEBM, etc.)"),
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  outputs="text",
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  title="🗣️ English Accent Classifier (Gradio Demo)",
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  description="Upload a short video clip of English speech. This tool predicts the English accent and confidence."