Processing latency is a critical issue for active noise control (ANC) due to the causality
constraint of ANC systems. This paper addresses low-latency ANC in the context of deep …

Most speech separation studies in monaural channel use only a single type of network, and
the separation effect is typically not satisfactory, posing difficulties for high quality speech …

Deep neural networks (DNN) have been successfully employed for the problem of monaural
sound source separation achieving state-of-the-art results. In this paper, we propose using …

Hearing aid users are challenged in listening situations with noise and especially speech-on-
speech situations with two or more competing voices. Specifically, the task of attending to …

Computer audition (ie, intelligent audio) has made great strides in recent years; however, it
is still far from achieving holistic hearing abilities, which more appropriately mimic human …

Mean square error (MSE) has been the preferred choice as loss function in the current deep
neural network (DNN) based speech separation techniques. In this paper, we propose a …

Processing latency is a critical issue for active noise control (ANC) due to the causality
constraint of ANC systems. This paper addresses low-latency ANC in the deep learning …

This paper proposes a low algorithmic latency adaptation of the deep clustering approach to
speaker-independent speech separation. It consists of three parts: a) the usage of long-short …

The purpose of this research is to develop a model that is able to perform real-time speaker
independent multi-talker speech separation task in time-domain using Time-Domain Audio …

We propose a method for noise reduction, the task of producing a clean audio signal from a
recording corrupted by ad-ditive noise. Many common approaches to this problem are …