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A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition
[article]
2020
arXiv
pre-print
This paper presents a transfer learning method in speech emotion recognition based on a Time-Delay Neural Network (TDNN) architecture. A major challenge in the current speech-based emotion detection research is data scarcity. The proposed method resolves this problem by applying transfer learning techniques in order to leverage data from the automatic speech recognition (ASR) task for which ample data is available. Our experiments also show the advantage of speaker-class adaptation modeling
arXiv:2008.02863v2
fatcat:ryklvv5r5rfllp7ovloaw4frse