Exploring speaker enrolment for few-shot personalisation in emotional vocalisation prediction. (arXiv:2206.06680v1 [cs.SD])

In this work, we explore a novel few-shot personalisation architecture for
emotional vocalisation prediction. The core contribution is an `enrolment'
encoder which utilises two unlabelled samples of the target speaker to adjust
the output of the emotion encoder; the adjustment is based on dot-product
attention, thus effectively functioning as a form of `soft' feature selection.
The emotion and enrolment encoders are based on two standard audio
architectures: CNN14 and CNN10. The two encoders are further guided to forget
or learn …

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