Speech enhancement and speech separation are two related tasks, whose purpose is to
extract either one or more target speech signals, respectively, from a mixture of sounds …

Perceiving a scene most fully requires all the senses. Yet modeling how objects look and
sound is challenging: most natural scenes and events contain multiple objects, and the …

Speech enhancement (SE) aims to reduce noise in speech signals. Most SE techniques
focus only on addressing audio information. In this paper, inspired by multimodal learning …

The separation of speech signals measured at multiple microphones in noisy and
reverberant environments using only the audio modality has limitations because there is …

In this paper, we review recent results on audiovisual (AV) fusion. We also discuss some of
the challenges and report on approaches to address them. One important issue in AV fusion …

Speaker diarization consists of assigning speech signals to people engaged in a dialogue.
An audio-visual spatiotemporal diarization model is proposed. The model is well suited for …

Speech separation aims to separate individual voices from an audio mixture of multiple
simultaneous talkers. Audio-only approaches show unsatisfactory performance when the …

The objective of private authentication for Radio Frequency Identification (RFID) systems is
to allow valid readers to explicitly authenticate their dominated tags without leaking the …

Source permutation, ie, assigning separated signal snippets to wrong sources over time, is a
major issue in the state-of-the-art speaker-independent speech source separation methods …

In this paper, we propose a novel method which is able to detect and separate audiovisual
sources present in a scene. Our method exploits the correlation between the video signal …