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  The model was trained on [MSP-Podcast](https://ecs.utdallas.edu/research/researchlabs/msp-lab/MSP-Podcast.html) for the Odyssey 2024 Emotion Recognition competition baseline<br>
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  This particular model is the multi-attributed based model which predict arousal, dominance and valence in a range of approximately 0...1.
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  For more details: [demo](https://huggingface.co/spaces/3loi/WavLM-SER-Multi-Baseline-Odyssey2024), [paper/soon]() and [GitHub](https://github.com/MSP-UTD/MSP-Podcast_Challenge/tree/main).
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  The model was trained on [MSP-Podcast](https://ecs.utdallas.edu/research/researchlabs/msp-lab/MSP-Podcast.html) for the Odyssey 2024 Emotion Recognition competition baseline<br>
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  This particular model is the multi-attributed based model which predict arousal, dominance and valence in a range of approximately 0...1.
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+ # Benchmarks
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+ CCC based on test3 and Development sets of the Odyssey Competition
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+ <table style="width:500px">
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+ <tr><th colspan=6 align="center" >Multi-Task Setup</th></tr>
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+ <tr><th colspan=3 align="center">Test 3</th><th colspan=3 align="center">Development</th></tr>
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+ <tr> <td>Val</td> <td>Dom</td> <td>Aro</td> <td>Val</td> <td>Dom</td> <td>Aro</td> </tr>
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+ <tr> <td> 0.577</td> <td>0.577</td> <td>0.405</td> <td>0.652</td> <td>0.688</td> <td>0.579</td> </tr>
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+ </table>
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  For more details: [demo](https://huggingface.co/spaces/3loi/WavLM-SER-Multi-Baseline-Odyssey2024), [paper/soon]() and [GitHub](https://github.com/MSP-UTD/MSP-Podcast_Challenge/tree/main).
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