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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 20; H. 22; S. 6688
Hauptverfasser:	Lee, Sanghyun, Han, David K., Ko, Hanseok
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 23.11.2020 MDPI
Schlagworte:	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
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!