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  # Empathic-Insight-Voice-Small
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  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1WR-B6j--Y5RdhIyRGF_tJ3YdFF8BkUA2)
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- **Empathic-Insight-Voice-Small** is a suite of 40+ emotion and attribute regression models trained on the large-scale, multilingual synthetic voice-acting dataset LAION'S GOT TALENT (~ 5.000 hours) & an "in the wild" dataset of voice snippets (also ~ 5.000 hours). 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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  This work is based on the research paper:
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  **"EMONET-VOICE: A Fine-Grained, Expert-Verified Benchmark for Speech Emotion Detection"**
 
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  # Empathic-Insight-Voice-Small
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  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1WR-B6j--Y5RdhIyRGF_tJ3YdFF8BkUA2)
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+ **Empathic-Insight-Voice-Small** is a suite of 40+ emotion and attribute regression models trained on the large-scale, multilingual synthetic voice-acting dataset LAION'S GOT TALENT (~ 5.000 hours) & an "in the wild" dataset of voice snippets (also ~ 5.000 hours). 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 (laion/BUD-E-Whisper) followed by dedicated MLP regression heads for each dimension.
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  This work is based on the research paper:
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  **"EMONET-VOICE: A Fine-Grained, Expert-Verified Benchmark for Speech Emotion Detection"**