Audio is an essential part of our life, but creating it often requires expertise and is time-
consuming. Research communities have made great progress over the past year advancing …

Universal source separation targets at separating the audio sources of an arbitrary mix,
removing the constraint to operate on a specific domain like speech or music. Yet, the …

Despite recent improvements in audio-text modeling, audio-text contrastive models still lag
behind their image-text counterparts in scale and performance. We propose a method to …

Audio-language models (ALMs) process sounds to provide a linguistic description of sound-
producing events and scenes. Recent advances in computing power and dataset creation …

We introduce a novel task named 'target speech diarization', which seeks to determine
'when target event occurred'within an audio signal. We devise a neural architecture called …

Abstract The Audio-Visual Video Parsing task aims to identify and temporally localize the
events that occur in either or both the audio and visual streams of audible videos. It often …

Extracting the speech of participants in a conversation amidst interfering speakers and noise
presents a challenging problem. In this paper, we introduce the novel task of target …

Despite significant recent progress across multiple subtasks of audio source separation, few
music source separation systems support separation beyond the four-stem vocals, drums …

Language-queried audio source separation (LASS) aims to separate an audio source
guided by a text query, with the signal-to-distortion ratio (SDR)-based metrics being …

Speech enhancement is crucial both for human and machine listening applications. Over the
last decade, the use of deep learning for speech enhancement has resulted in tremendous …