An Interaction-aware Attention Network for Speech Emotion Recognition in Spoken Dialogs
In this work, we propose an interaction-aware attention network (IAAN) that incorporate contextual information in the learned vocal representation through a novel attention mechanism. Our proposed method achieves 66.3% accuracy (7.9% over baseline methods) in four class emotion recognition and is also the current state-of-art recognition rates obtained on the benchmark database IEMOCAP.
Code (1)
Tasks
Emotion RecognitionSpeech Emotion RecognitionSimilar Papers 제목 키워드 기반
Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking Model
Emotion plays a fundamental role in human interaction, and therefore systems capable of identifying emotions in speech are crucial in the context of human-computer interaction. Speech emotion recognition (SER) is a chall…
Emotion RecognitionSpeech Emotion RecognitionConvolutional Attention Networks for Multimodal Emotion Recognition from Speech and Text Data
Emotion recognition has become a popular topic of interest, especially in the field of human computer interaction. Previous works involve unimodal analysis of emotion, while recent efforts focus on multi-modal emotion re…
Emotion RecognitionMultimodal Emotion RecognitionSemantic Differentiation in Speech Emotion Recognition: Insights from Descriptive and Expressive Speech Roles
Speech Emotion Recognition (SER) is essential for improving human-computer interaction, yet its accuracy remains constrained by the complexity of emotional nuances in speech. In this study, we distinguish between descrip…
Speech Emotion RecognitionAttention Based Fully Convolutional Network for Speech Emotion Recognition
Speech emotion recognition is a challenging task for three main reasons: 1) human emotion is abstract, which means it is hard to distinguish; 2) in general, human emotion can only be detected in some specific moments dur…
Emotion RecognitionSpeech Emotion RecognitionTransfer LearningMFHCA: Enhancing Speech Emotion Recognition Via Multi-Spatial Fusion and Hierarchical Cooperative Attention
Speech emotion recognition is crucial in human-computer interaction, but extracting and using emotional cues from audio poses challenges. This paper introduces MFHCA, a novel method for Speech Emotion Recognition using M…
Emotion RecognitionSpeech Emotion Recognition