Self-supervised Learning for Speech Emotion Recognition Task Using Audio-visual Features and Distil Hubert Model on BAVED and RAVDESS Databases

Existing pre-trained models like Distil HuBERT excel at uncovering hidden patterns and facilitating accurate recognition across diverse data types, such as audio and visual information. We harnessed this capability to develop a deep learning model that utilizes Distil HuBERT for jointly learning the...

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Veröffentlicht in:	Journal of systems science and systems engineering 2024-10, Vol.33 (5), p.576-606
Hauptverfasser:	Dabbabi, Karim, Mars, Abdelkarim
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Audio data Complexity Deep learning Economic Theory/Quantitative Economics/Mathematical Methods Emotion recognition Emotions Engineering Feature recognition Operations Research/Decision Theory Pattern recognition Real time Self-supervised learning Speech recognition Visual tasks
Online-Zugang:	Volltext
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