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  ## Example Video Analyses (Top 3 Emotions)
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  <!-- This section will be populated by the HTML from Cell 0 -->
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- {{<div style='display: flex; flex-wrap: wrap; justify-content: flex-start; gap: 15px;'>
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  <div style='flex: 0 1 auto; margin-bottom: 15px; text-align: center; width: 480px; max-width: 480px;'>
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  <a href='https://www.youtube.com/watch?v=TsTVKCmqHhk' target='_blank' title='Watch video TsTVKCmqHhk'>
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  <img src='https://img.youtube.com/vi/TsTVKCmqHhk/hqdefault.jpg' alt='YouTube Thumbnail for TsTVKCmqHhk' style='width: 100%; height: auto; border: 1px solid #ccc; border-radius: 4px; display: block;'>
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  </a>
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  <p style='font-size: 0.8em; margin-top: 5px; word-break: break-all;'>ID: dDrmjcUq8W4</p>
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  </div>
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  **Empathic-Insight-Voice-Small** is a suite of 40+ emotion and attribute regression models trained on the EMONET-VOICE benchmark dataset, which is derived from the large-scale, multilingual synthetic voice-acting dataset LAION'S GOT TALENT. Each model is designed to predict the intensity of a specific fine-grained emotion or attribute from speech audio. These models leverage embeddings from a fine-tuned Whisper model (mkrausio/EmoWhisper-AnS-Small-v0.1) followed by dedicated MLP regression heads for each dimension.
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  ## Example Video Analyses (Top 3 Emotions)
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  <!-- This section will be populated by the HTML from Cell 0 -->
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+ <div style='display: flex; flex-wrap: wrap; justify-content: flex-start; gap: 15px;'>
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  <div style='flex: 0 1 auto; margin-bottom: 15px; text-align: center; width: 480px; max-width: 480px;'>
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  <a href='https://www.youtube.com/watch?v=TsTVKCmqHhk' target='_blank' title='Watch video TsTVKCmqHhk'>
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  <img src='https://img.youtube.com/vi/TsTVKCmqHhk/hqdefault.jpg' alt='YouTube Thumbnail for TsTVKCmqHhk' style='width: 100%; height: auto; border: 1px solid #ccc; border-radius: 4px; display: block;'>
 
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  </a>
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  <p style='font-size: 0.8em; margin-top: 5px; word-break: break-all;'>ID: dDrmjcUq8W4</p>
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  </div>
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+ </div>
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  **Empathic-Insight-Voice-Small** is a suite of 40+ emotion and attribute regression models trained on the EMONET-VOICE benchmark dataset, which is derived from the large-scale, multilingual synthetic voice-acting dataset LAION'S GOT TALENT. Each model is designed to predict the intensity of a specific fine-grained emotion or attribute from speech audio. These models leverage embeddings from a fine-tuned Whisper model (mkrausio/EmoWhisper-AnS-Small-v0.1) followed by dedicated MLP regression heads for each dimension.
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