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import os |
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import subprocess |
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import sys |
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try: |
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import yt_dlp as youtube_dl |
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except ImportError: |
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subprocess.check_call([sys.executable, "-m", "pip", "install", "yt-dlp"]) |
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import yt_dlp as youtube_dl |
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import gradio as gr |
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from transformers import pipeline |
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def download_video(video_url, filename="downloaded_video.mp4"): |
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ydl_opts = { |
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'format': 'bestaudio/best', |
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'outtmpl': filename, |
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'noplaylist': True, |
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'quiet': True, |
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'user_agent': ( |
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'Mozilla/5.0 (Windows NT 10.0; Win64; x64) ' |
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'AppleWebKit/537.36 (KHTML, like Gecko) ' |
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'Chrome/115.0.0.0 Safari/537.36' |
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) |
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} |
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with youtube_dl.YoutubeDL(ydl_opts) as ydl: |
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ydl.download([video_url]) |
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return filename |
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def extract_audio(video_filename, audio_filename="extracted_audio.wav"): |
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command = [ |
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"ffmpeg", |
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"-y", |
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"-i", video_filename, |
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"-vn", |
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"-acodec", "pcm_s16le", |
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"-ar", "16000", |
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"-ac", "1", |
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audio_filename |
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] |
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subprocess.run(command, check=True) |
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return audio_filename |
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def classify_accent(audio_file, model_name="superb/wav2vec2-base-superb-sid"): |
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classifier = pipeline("audio-classification", model=model_name) |
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results = classifier(audio_file) |
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if results: |
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top = results[0] |
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return f"Speaker ID (as accent proxy): {top['label']}\nConfidence: {top['score'] * 100:.2f}%" |
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return "No result." |
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def accent_classifier(video_url): |
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try: |
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video_file = download_video(video_url) |
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audio_file = extract_audio(video_file) |
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result = classify_accent(audio_file) |
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except Exception as e: |
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result = f"Error occurred: {e}" |
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finally: |
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for f in ["downloaded_video.mp4", "extracted_audio.wav"]: |
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if os.path.exists(f): |
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os.remove(f) |
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return result |
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iface = gr.Interface( |
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fn=accent_classifier, |
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inputs=gr.Textbox(label="Video URL", placeholder="Paste a public YouTube or Vimeo video link here"), |
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outputs="text", |
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title="Accent Classifier", |
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description="Download a video, extract the audio, and classify the speaker (as an accent proxy) using a Hugging Face model." |
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) |
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if __name__ == "__main__": |
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iface.launch() |
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