Papers with first universal representation model

1 papers
emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation (2024.findings-acl)

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Challenge: Existing models for speech emotion recognition are not suitable for emotional tasks.
Approach: They propose a universal speech emotion representation model that is pre-trained on open-source emotion data.
Outcome: euphoria2vec outperforms state-of-the-art models and emotion specialist models . it shows consistent improvements among 10 different languages of speech emotion recognition datasets .

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