Abstract Audio-Visual Emotion Recognition (AVER) has garnered increasing attention in
recent years for its critical role in creating emotion-aware intelligent machines. Previous …

The Spoken Language Understanding Evaluation (SLUE) suite of benchmark tasks was
recently introduced to address the need for open resources and benchmarking of complex …

This study introduces the first single branch network designed to tackle a spectrum of
biometric matching scenarios, including unimodal, multimodal, cross-modal, and missing …

Smart cities deploy various sensors such as microphones and RGB cameras to collect data
to improve the safety and comfort of the citizens. As data annotation is expensive, self …

Audio-visual pre-trained models have gained substantial attention recently and
demonstrated superior performance on various audio-visual tasks. This study investigates …

Self-supervised learning (SSL), an unsupervised representation learning technique, has
received widespread attention across various modalities. Speech, with its inherent …

Thanks to the rise of deep learning and the availability of large-scale audio-visual
databases, recent advances have been achieved in Visual Speech Recognition (VSR) …

This paper presents a novel approach to processing multimodal data for dynamic emotion
recognition, named as the Multimodal Masked Autoencoder for Dynamic Emotion …

Video-to-audio (V2A) generation aims to synthesize content-matching audio from silent
video, and it remains challenging to build V2A models with high generation quality …