Fusion-ConvBERT: Parallel Convolution and BERT Fusion for Speech Emotion Recognition

Speech emotion recognition predicts the emotional state of a speaker based on the person’s speech. It brings an additional element for creating more natural human–computer interactions. Earlier studies on emotional recognition have been primarily based on handcrafted features and manual labels. With...

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Vydáno v:	Sensors (Basel, Switzerland) Ročník 20; číslo 22; s. 6688
Hlavní autoři:	Lee, Sanghyun, Han, David K., Ko, Hanseok
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 23.11.2020 MDPI
Témata:	Accuracy bidirectional encoder representations from transformers (BERT) convolutional neural networks (CNNs) Deep learning Emotions Experiments Humans Neural networks Neural Networks, Computer representation Signal processing spatiotemporal representation Speech speech emotion recognition transformer bidirectional encoder representations from transformers (BERT) convolutional neural networks (CNNs) speech emotion recognition fusion model transformer representation spatiotemporal representation
ISSN:	1424-8220, 1424-8220
On-line přístup:	Získat plný text
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