Prior studies on audio-visual speech recognition typically assume the visibility of speaking
lips, ignoring the fact that visual occlusion occurs in real-world videos, thus adversely …

Humans possess the remarkable ability to selectively attend to a single speaker amidst
competing voices and background noise, known as selective auditory attention. Recent …

Visual information can serve as an effective cue for target speaker extraction (TSE) and is
vital to improving extraction performance. In this paper, we propose AV-SepFormer, a …

Speaker extraction aims to selectively extract the target speaker from the multi-talker
environment under the guidance of auxiliary reference. Recent studies have shown that the …

Speaker extraction seeks to extract the clean speech of a target speaker from a multi-talker
mixture speech. There have been studies to use a pre-recorded speech sample or face …

End-to-end time-domain speech separation with masking strategy has shown its
performance advantage, where a 1-D convolutional layer is used as the speech encoder to …

Neuro-steered speaker extraction aims to extract the listener's brainattended speech signal
from a multi-talker speech signal, in which the attention is derived from the cortical activity …

The Audio-Visual Speaker Extraction (AVSE) algorithm employs parallel video recording to
leverage two visual cues, namely speaker identity and synchronization, to enhance …

Speaker extraction and diarization are two enabling techniques for real-world speech
applications. Speaker extraction aims to extract a target speaker's voice from a speech …

Speaker extraction (SE) aims to segregate the speech of a target speaker from a mixture of
interfering speakers with the help of auxiliary information. Several forms of auxiliary …