Meta-training a speech-language model with in-context learning lets it recognize emotions for unseen speakers using just a few labeled utterances from that speaker, outperforming prior enrollment-based methods on a new 800-speaker Japanese dataset.
Affect intensity as an individual difference characteristic: A review,
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Few-shot Personalization via In-Context Learning for Speech Emotion Recognition based on Speech-Language Model
Meta-training a speech-language model with in-context learning lets it recognize emotions for unseen speakers using just a few labeled utterances from that speaker, outperforming prior enrollment-based methods on a new 800-speaker Japanese dataset.