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README.md
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tags:
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- model_hub_mixin
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- pytorch_model_hub_mixin
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---
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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- Library: https://github.com/tiantiaf0627/vox-profile-release
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- Docs: [More Information Needed]
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tags:
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- model_hub_mixin
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- pytorch_model_hub_mixin
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license: apache-2.0
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language:
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- en
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metrics:
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- accuracy
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base_model:
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- openai/whisper-large-v3
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pipeline_tag: audio-classification
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---
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# Whisper-Large V3 for Categorical Emotion Classification
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# Model Description
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This model includes the implementation of categorical emotion classification described in Vox-Profile: A Speech Foundation Model Benchmark for Characterizing Diverse Speaker and Speech Traits (https://arxiv.org/pdf/2505.14648)
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The training pipeline used is also the top performing solution (SAILER) in INTERSPEECH 2025 - Speech Emotion Challenge (https://lab-msp.com/MSP-Podcast_Competition/IS2025/). Note that we did not use all the augmentation and and did not use the transcript to make the model simple but still effective.
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We use the MSP-Podcast data for training this model. Noting that the model might be sensitive to content information in making the emotion prediction.
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The included emotions are:
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<pre>
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[
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'Anger',
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'Contempt',
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'Disgust',
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'Fear',
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'Happiness',
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'Neutral',
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'Sadness',
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'Surprise',
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'Other'
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]
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</pre>
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- Library: https://github.com/tiantiaf0627/vox-profile-release
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- Docs: [More Information Needed]
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