The cocktail party problem, ie, tracing and recognizing the speech of a specific speaker
when multiple speakers talk simultaneously, is one of the critical problems yet to be solved …

Recent progress in separating the speech signals from multiple overlapping speakers using
a single audio channel has brought us closer to solving the cocktail party problem. However …

This paper addresses the problem of single channel speech recognition of a target speaker
in a mixture of speech signals. We propose to exploit auxiliary speaker information provided …

Speaker-aware source separation methods are promising workarounds for major difficulties
such as arbitrary source permutation and unknown number of sources. However, it remains …

Speech perception in crowded environments is challenging for hearing-impaired listeners.
Assistive hearing devices cannot lower interfering speakers without knowing which speaker …

Deep learning-based single-channel source separation algorithms are currently being
actively investigated. Among them, Deep Clustering (DC) and Deep Attractor Networks …

We address the problem of speaker counting and separation from a noisy, single-channel,
multi-source, recording. Most of the works in the literature assume mixtures containing two to …

Future wearable technology may provide for enhanced communication in noisy
environments and for the ability to pick out a single talker of interest in a crowded room …

Monaural speech separation is the task of separating target speech from interference in
single-channel recordings. Although substantial progress has been made recently in deep …

In daily listening environments, speech is always distorted by background noise, room
reverberation and interference speakers. With the developing of deep learning approaches …