Ricard Marxer
TitleCited byYear
The third ‘CHiME’speech separation and recognition challenge: Dataset, task and baselines
J Barker, R Marxer, E Vincent, S Watanabe
2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015
3602015
An analysis of environment, microphone and data simulation mismatches in robust speech recognition
E Vincent, S Watanabe, AA Nugraha, J Barker, R Marxer
Computer Speech & Language 46, 535-557, 2017
1462017
The third ‘CHiME’speech separation and recognition challenge: Analysis and outcomes
J Barker, R Marxer, E Vincent, S Watanabe
Computer Speech & Language 46, 605-626, 2017
392017
Computational models of music perception and cognition I: The perceptual and cognitive processing chain
H Purwins, P Herrera, M Grachten, A Hazan, R Marxer, X Serra
Physics of Life Reviews 5 (3), 151-168, 2008
332008
Computational models of music perception and cognition II: Domain-specific music processing
H Purwins, M Grachten, P Herrera, A Hazan, R Marxer, X Serra
Physics of Life Reviews 5 (3), 169-182, 2008
272008
Evaluation and combination of pitch estimation methods for melody extraction in symphonic classical music
JJ Bosch, R Marxer, E Gómez
Journal of New Music Research 45 (2), 101-117, 2016
23*2016
Low-latency instrument separation in polyphonic audio using timbre models
R Marxer, J Janer, J Bonada
International Conference on Latent Variable Analysis and Signal Separation …, 2012
232012
Knowledge transfer between speakers for personalised dialogue management
I Casanueva, T Hain, H Christensen, R Marxer, P Green
Proceedings of the 16th Annual Meeting of the Special Interest Group on …, 2015
222015
What/when causal expectation modelling applied to audio signals
A Hazan, R Marxer, P Brossier, H Purwins, P Herrera, X Serra
Connection Science 21 (2-3), 119-143, 2009
172009
Dynamical hierarchical self-organization of harmonic, motivic, and pitch categories
R Marxer, P Holonowicz, H Purwins, A Hazan
Music, Brain and Cognition. Part 2, 2007
172007
Score-informed and timbre independent lead instrument separation in real-world scenarios
JJ Bosch, K Kondo, R Marxer, J Janer
2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO …, 2012
162012
The 4th CHiME speech separation and recognition challenge
E Vincent, S Watanabe, J Barker, R Marxer
CHiME CHALLENGE, 2016
122016
The CHiME challenges: Robust speech recognition in everyday environments
JP Barker, R Marxer, E Vincent, S Watanabe
New Era for Robust Speech Recognition, 327-344, 2017
112017
Separation of unvoiced fricatives in singing voice mixtures with semi-supervised NMF
J Janer, R Marxer
Proc. 16th Int. Conf. Digital Audio Effects, 2-5, 2013
112013
Exploiting synchrony spectra and deep neural networks for noise-robust automatic speech recognition
N Ma, R Marxer, J Barker, GJ Brown
2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015
102015
Music classification using high-level models
N Wack, C Laurier, O Meyers, R Marxer, D Bogdanov, J Serra, E Gómez, ...
Music Information Retrieval Evaluation Exchange (MIREX’10), 2010
102010
An f-measure for evaluation of unsupervised clustering with non-determined number of clusters
R Marxer, H Purwins, A Hazan
Report of the EmCAP project (European Commission FP6-IST), 1-3, 2008
102008
Unsupervised incremental online learning and prediction of musical audio signals
R Marxer, H Purwins
IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (5), 863-874, 2016
92016
Technique for suppressing particular audio component
J Bonada, J Janer, R Marxer, Y Umeyama, K Kondo
US Patent 9,070,370, 2015
82015
DNN driven speaker independent audio-visual mask estimation for speech separation
M Gogate, A Adeel, R Marxer, J Barker, A Hussain
arXiv preprint arXiv:1808.00060, 2018
72018
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Articles 1–20