Audio-visual speech recognition (AVSR) is one of the most promising solutions for reliable
speech recognition, particularly when audio is corrupted by noise. Additional visual …

Recommender systems (RSs) provide customers with a personalized navigation experience
within the vast catalogs of products and services offered on popular online platforms …

Automatic audio-visual expression recognition can play an important role in communication
services such as tele-health, VOIP calls and human-machine interaction. Accuracy of audio …

Cross-resolution image alignment is a key problem in multiscale gigapixel photography,
which requires to estimate homography matrix using images with large resolution gap …

Current deep learning approaches for multimodal fusion rely on bottom-up fusion of high
and mid-level latent modality representations (late/mid fusion) or low level sensory inputs …

Emotion recognition using audiovisual features is a challenging task for human-machine
interaction systems. Under ideal conditions (perfect illumination, clean speech signals, and …

Audiovisual automatic speech recognition (AV-ASR) aims to improve the robustness of a
speech recognition system by incorporating visual information. Training fully supervised …

Emotion recognition is a challenging task due to limited availability of in-the-wild labeled
datasets. Self-supervised learning has shown improvements on tasks with limited labeled …

Humans show a remarkable perceptual ability to select the speech stream of interest among
multiple competing speakers. Previous studies demonstrated that auditory attention …

We present a Conformer-based end-to-end neural diarization (EEND) model that uses both
acoustic input and features derived from an automatic speech recognition (ASR) model. Two …