The article introduces DSNet, a Disentangled Siamese Network with neutral calibration for speech emotion recognition (SER). DSNet aims to address the challenges in SER, such as the unconscious encoding of…
Continue readingThe research explores the use of models such as BERT and HuBERT in dimensional speech emotion recognition. Despite their large dimensionality, these models are frequently used for emotion recognition tasks,…
Continue readingThis research article discusses the development of a frame-level emotional state alignment method for speech emotion recognition (SER). The authors fine-tune the HuBERT model to create a SER system with…
Continue readingThe study focuses on improving Speech Emotion Recognition (SER) which is crucial in human-machine interaction. Existing SER methods overlook the information gap between the pre-training speech recognition task and the…
Continue readingThe article focuses on Speech Emotion Recognition (SER), an essential tool in enhancing human-computer interaction by understanding emotional states. The authors propose a novel approach that combines self-supervised feature extraction…
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