Strong Generalized Speech Emotion Recognition Based on Effective Data Augmentation

The absence of labeled samples limits the development of speech emotion recognition (SER). Data augmentation is an effective way to address sample sparsity. However, there is a lack of research on data augmentation algorithms in the field of SER. In this paper, the effectiveness of classical acousti...

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書誌詳細

主要な著者:	Huawei Tao, Shuai Shan, Ziyi Hu, Chunhua Zhu, Hongyi Ge
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2022-12-01
シリーズ:	Entropy
主題:	speech emotion recognition data augmentation multi-channel feature extractor Wasserstein distance feature distributions speaker-invariant emotional representations
オンライン･アクセス:	https://www.mdpi.com/1099-4300/25/1/68
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