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Found 5 papers, 1 papers with code
TRNet: Two-level Refinement Network leveraging Speech Enhancement for Noise Robust Speech Emotion Recognition
One persistent challenge in Speech Emotion Recognition (SER) is the ubiquitous environmental noise, which frequently results in diminished SER performance in practical use.
Modality-Collaborative Transformer with Hybrid Feature Reconstruction for Robust Emotion Recognition
As a vital aspect of affective computing, Multimodal Emotion Recognition has been an active research area in the multimedia community.
DSNet: Disentangled Siamese Network with Neutral Calibration for Speech Emotion Recognition
One persistent challenge in deep learning based speech emotion recognition (SER) is the unconscious encoding of emotion-irrelevant factors (e. g., speaker or phonetic variability), which limits the generalization of SER in practical use.
Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy
Recently, audio-visual scene classification (AVSC) has attracted increasing attention from multidisciplinary communities.
CTA-RNN: Channel and Temporal-wise Attention RNN Leveraging Pre-trained ASR Embeddings for Speech Emotion Recognition
To further exploit the embeddings from different layers of the ASR encoder, we propose a novel CTA-RNN architecture to capture the emotional salient parts of embeddings in both the channel and temporal directions.
