Over the past decades, a tremendous amount of research has been done on the use of
machine learning for speech processing applications, especially speech recognition …

Eliminating the negative effect of non-stationary environmental noise is a long-standing
research topic for automatic speech recognition but still remains an important challenge …

The CHiME challenge series aims to advance far field speech recognition technology by
promoting research at the interface of signal processing and automatic speech recognition …

Speech enhancement and automatic speech recognition (ASR) are most often evaluated in
matched (or multi-condition) settings where the acoustic conditions of the training data …

This article addresses the problem of multichannel audio source separation. We propose a
framework where deep neural networks (DNNs) are used to model the source spectra and …

This paper deals with the separation of music into individual instrument tracks which is
known to be a challenging problem. We describe two different deep neural network …

Popular music is often composed of an accompaniment and a lead component, the latter
typically consisting of vocals. Filtering such mixtures to extract one or both components has …

This paper presents the design and outcomes of the CHiME-3 challenge, the first open
speech recognition evaluation designed to target the increasingly relevant multichannel …

Abstract Galvanised Steel Pipe (GSP) is the most common gas pipeline in populated areas.
Existing leak detection research aimed at welded steel pipe is not suitable for GSP system …

This article addresses the problem of multichannel music separation. We propose a
framework where the source spectra are estimated using deep neural networks and …