背景噪声下通过自监督声语义融合和交叉注意进行强大的语音情感识别

Human speech carries information about both the words being spoken and the emotions behind them. Speech Emotion Recognition (SER) uses artificial intelligence to identify emotions such as happiness, sadness, anger, and neutrality from a person's voice. However, recognizing emotions accurately is difficult when speech contains background noise or when different people express the same emotion in different ways. This paper proposes a speech emotion recognition framework that combines self-supervised speech representations with acoustic features through cross-attention. A pretrained speech encode