Speech recognition using deep neural networks: A systematic review
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 …
machine learning for speech processing applications, especially speech recognition …
Deep learning for environmentally robust speech recognition: An overview of recent developments
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 …
research topic for automatic speech recognition but still remains an important challenge …
The third 'CHiME'speech separation and recognition challenge: Dataset, task and baselines
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 …
promoting research at the interface of signal processing and automatic speech recognition …
An analysis of environment, microphone and data simulation mismatches in robust 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 …
matched (or multi-condition) settings where the acoustic conditions of the training data …
Multichannel audio source separation with deep neural networks
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 …
framework where deep neural networks (DNNs) are used to model the source spectra and …
Improving music source separation based on deep neural networks through data augmentation and network blending
S Uhlich, M Porcu, F Giron, M Enenkl… - … on acoustics, speech …, 2017 - ieeexplore.ieee.org
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 …
known to be a challenging problem. We describe two different deep neural network …
An overview of lead and accompaniment separation in music
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 …
typically consisting of vocals. Filtering such mixtures to extract one or both components has …
The third 'CHiME'speech separation and recognition challenge: Analysis and outcomes
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 …
speech recognition evaluation designed to target the increasingly relevant multichannel …
Gas leak detection in galvanised steel pipe with internal flow noise using convolutional neural network
Y Song, S Li - Process Safety and Environmental Protection, 2021 - Elsevier
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 …
Existing leak detection research aimed at welded steel pipe is not suitable for GSP system …
Multichannel music separation with deep neural networks
This article addresses the problem of multichannel music separation. We propose a
framework where the source spectra are estimated using deep neural networks and …
framework where the source spectra are estimated using deep neural networks and …