Self-Attention-Based Masked Spectrogram Generation and Self-Supervised Learning Method for Improving Speech Emotion Recognition

In this paper, we propose the Self-Attention-based Masked Spectrogram Generation (SAMSG) method to address the problem of model overfitting and improve generalization performance in speech emotion recognition under limited data conditions. A key challenge in many emotional speech datasets is that a...

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Detalhes bibliográficos

Principais autores:	Jeong-Yoon Kim, Seung-Ho Lee
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2025-01-01
coleção:	IEEE Access
Assuntos:	Speech emotion recognition self-attention-based masked spectrogram generation self-supervised learning vision transformer
Acesso em linha:	https://ieeexplore.ieee.org/document/11126069/
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