Improving the Dependency on Fine-Tuning Data in Transfer Learning for Speech Emotion Recognition

Ricardo García, Rodrigo Mahu, Carlos Busso +1

Compensating for train-test mismatches in acoustic environments is important for deployable speech solutions. This paper proposes to reduce the amount of fine-tuning data needed in…