8 accepted papers
Generative models have attracted considerable attention for speech separation tasks, and among these, diffusion-based methods are being explored. Despite the notable success of diffusion techniques in generation tasks, their adaptation to speech separation has encountered challenges, notably slow co…
Sound Event Detection (SED) often employs pre-trained models to address data scarcity issues. However, existing systems usually treat the pretrained models as frozen feature extractors, resulting in suboptimal efficiency, or fully fine-tune the pretrained models, which requires substantial computati…
Group Emotion Recognition (GER) seeks to identify emotional states within multi-person groups. The complexity of the environment and the reliance on a single group emotion label often result in noisy individuals with inconsistent emotional expressions, hampering accurate emotion classification. Main…
Video Character Social Relationship Recognition (VCSRR) requires a comprehensive consideration about spatio-temporal and multi-modal clues in videos. Most existing methods mainly focus on integrating multi-modal clues and modeling interactions among characters. However, they fail to discover key clu…
Recently, the segmented sample-level modeling approach based on Dual-Path Recurrent Neural Network (DPRNN) has been proved to be effective in Monaural Speech Separation (MSS). Many dual-path networks such as Dual-Path Transformer Network (DPTNet), with a series of improvements to DPRNN, have also im…
Recently, speaker verification (SV) techniques relay on deep learning frameworks to extract more informative embedding vectors, which greatly improves the accuracy compared with traditional machine learning methods. The well-known x-vector architecture, a time delay neural network (TDNN), is widely…
Facial expression recognition (FER) is a challenging task due to different expressions under arbitrary poses. Most conventional approaches either perform face frontalization on a non-frontal facial image or learn separate classifiers for each pose. Different from existing methods, in this paper, we…
In speech emotion recognition (SER), speech data is usually captured from different scenarios, which often leads to significant performance degradation due to the inherent mismatch between training and test set. To cope with this problem, we propose a domain adaptation method called Sharing Priors b…