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Andrew J.R. Simpson, PhD
Andrew J.R. Simpson, PhD
Research Fellow, CVSSP, University of Surrey
Verified email at surrey.ac.uk
Title
Cited by
Cited by
Year
Deep karaoke: Extracting vocals from musical mixtures using a convolutional deep neural network
AJR Simpson, G Roma, MD Plumbley
Latent Variable Analysis and Signal Separation: 12th International …, 2015
1612015
Self-driving car steering angle prediction based on image recognition
S Du, H Guo, A Simpson
arXiv preprint arXiv:1912.05440, 2019
992019
Two-stage single-channel audio source separation using deep neural networks
EM Grais, G Roma, AJR Simpson, MD Plumbley
IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (9), 1773 …, 2017
562017
Single-channel audio source separation using deep neural network ensembles
EM Grais, G Roma, AJR Simpson, MD Plumbley
Audio Engineering Society Convention 140, 2016
472016
The mathematics of mixing
M Terrell, A Simpson, M Sandler
Journal of the audio engineering society 62 (1/2), 4-13, 2014
342014
Probabilistic binary-mask cocktail-party source separation in a convolutional deep neural network
AJR Simpson
arXiv preprint arXiv:1503.06962, 2015
322015
Abstract learning via demodulation in a deep neural network
AJR Simpson
arXiv preprint arXiv:1502.04042, 2015
322015
Combining Mask Estimates for Single Channel Audio Source Separation Using Deep Neural Networks.
EM Grais, G Roma, AJR Simpson, MD Plumbley
INTERSPEECH, 3339-3343, 2016
312016
Visual objects in the auditory system in sensory substitution: how much information do we need?
DJ Brown, AJR Simpson, MJ Proulx
Multisensory Research 27 (5-6), 337-357, 2014
282014
Over-sampling in a deep neural network
AJR Simpson
arXiv preprint arXiv:1502.03648, 2015
232015
Syncopation and the score
C Song, AJR Simpson, CA Harte, MT Pearce, MB Sandler
PLoS One 8 (9), e74692, 2013
222013
Selective adaptation to “oddball” sounds by the human auditory system
AJR Simpson, NS Harper, JD Reiss, D McAlpine
Journal of Neuroscience 34 (5), 1963-1969, 2014
202014
Discriminative enhancement for single channel audio source separation using deep neural networks
EM Grais, G Roma, AJR Simpson, MD Plumbley
Latent Variable Analysis and Signal Separation: 13th International …, 2017
192017
Evaluation of audio source separation models using hypothesis-driven non-parametric statistical methods
AJR Simpson, G Roma, EM Grais, RD Mason, C Hummersone, A Liutkus, ...
2016 24th European Signal Processing Conference (EUSIPCO), 1763-1767, 2016
142016
A practical step-by-step guide to the time-varying loudness model of Moore, Glasberg, and Baer (1997; 2002)
AJR Simpson, MJ Terrell, JD Reiss
Audio Engineering Society Convention 134, 2013
132013
The dynamic range paradox: a central auditory model of intensity change detection
AJR Simpson, JD Reiss
PLoS One 8 (2), e57497, 2013
122013
Music remixing and upmixing using source separation
G Roma, EM Grais, AJR Simpson, MD Plumbley
Proceedings of the 2nd AES Workshop on Intelligent Music Production 13, 2016
112016
Untwist: A new toolbox for audio source separation
G Roma, EM Grais, AJ Simpson, I Sobieraj, MD Plumbley
Extended abstracts for the late-breaking demo session of the 17th …, 2016
112016
Auditory scene analysis and sonified visual images. Does consonance negatively impact on object formation when using complex sonified stimuli?
DJ Brown, AJR Simpson, MJ Proulx
Frontiers in psychology 6, 1522, 2015
112015
Dither is better than dropout for regularising deep neural networks
AJR Simpson
arXiv preprint arXiv:1508.04826, 2015
112015
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