One of the most amazing functions of the human auditory system is the ability to detect all
kinds of sound events in the environment. With the technologies and hardware advances …

In recent years, rapid progress has been made on the problem of single-channel sound
separation using supervised training of deep neural networks. In such supervised …

In this paper, we present an efficient neural network for end-to-end general purpose audio
source separation. Specifically, the backbone structure of this convolutional network is the …

The machine recognition of speech spoken at a distance from the microphones, known as
far-field automatic speech recognition (ASR), has received a significant increase in attention …

We introduce the Free Universal Sound Separation (FUSS) dataset, a new corpus for
experiments in separating mixtures of an unknown number of sounds from an open domain …

We introduce AudioScopeV2, a state-of-the-art universal audio-visual on-screen sound
separation system which is capable of learning to separate sounds and associate them with …

Audio-visual segmentation is a challenging task that aims to predict pixel-level masks for
sound sources in a video. Previous work applied a comprehensive manually designed …

Recent progress in deep learning has enabled many advances in sound separation and
visual scene understanding. However, extracting sound sources which are apparent in …

In this paper, we introduce the task of language-queried audio source separation (LASS),
which aims to separate a target source from an audio mixture based on a natural language …

We introduce the active audio-visual source separation problem, where an agent must move
intelligently in order to better isolate the sounds coming from an object of interest in its …