Ricard Marxer

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Jon P Barkercomputer science, university of sheffieldVerified email at sheffield.ac.uk
Shinji WatanabeCarnegie Mellon UniversityVerified email at cmu.edu
Emmanuel VincentSenior Research Scientist, InriaVerified email at inria.fr
Hendrik PurwinsCenter of Excellence for LLMs and GenAI, AccentureVerified email at accenture.com
Jan ChorowskiPathway (past: MSR, MILA, Google Brain)Verified email at pathway.com
Jordi JanerMusic Technology Group, Universitat Pompeu FabraVerified email at upf.edu
Perfecto Herrera-BoyerMusic Technology Group, Universitat Pompeu FabraVerified email at upf.edu
Phil GreenProfessor of Computer Science, University of SheffieldVerified email at dcs.shef.ac.uk
Heidi ChristensenUniversity of SheffieldVerified email at sheffield.ac.uk
Roger K. MooreProfessor of Spoken Language Processing, Sheffield UniversityVerified email at sheffield.ac.uk
Xavier SerraDepartment of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), BarcelonaVerified email at upf.edu
Aditya Arie NugrahaRIKEN Center for Advanced Intelligence Project (AIP)Verified email at postman.riken.jp
Lorenzo DesideriCentre for Assistive Technology - BolognaVerified email at ausilioteca.org
Massimiliano MalavasiRegional Centre for Assistive TechnologyVerified email at ausilioteca.org
Prof Amir HussainSchool of Computing, Edinburgh Napier University, Scotland, UKVerified email at napier.ac.uk
Frank RudziczDalhousie University, Computer Science ; Vector Institute for Artificial IntelligenceVerified email at dal.ca
Maarten GrachtenIndependent Machine Learning ConsultantVerified email at grachten.eu
Juan J. BoschSpotifyVerified email at spotify.com
Andre CoyUniversity of the West IndiesVerified email at uwimona.edu.jm
Emilia GómezJoint Research Centre, European Commission and Music Technology Group, Universitat Pompeu FabraVerified email at upf.edu

Ricard Marxer

Université de Toulon, Aix Marseille Univ, CNRS, LIS

Verified email at univ-tln.fr - Homepage

machine learning audio processing robotics computer vision


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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	768	2015
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	418	2017
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	140	2017
A corpus of audio-visual Lombard speech with frontal and profile views N Alghamdi, S Maddock, R Marxer, J Barker, GJ Brown The Journal of the Acoustical Society of America 143 (6), EL523-EL529, 2018	100	2018
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	54	2016
The 4th CHiME speech separation and recognition challenge E Vincent, S Watanabe, J Barker, R Marxer URL: http://spandh. dcs. shef. ac. uk/chime_challenge/(last accessed on 1 …, 2016	53	2016
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	49	2018
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	49	2008
Robust training of vector quantized bottleneck models A Łańcucki, J Chorowski, G Sanchez, R Marxer, N Chen, HJGA Dolfing, ... 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020	43	2020
The impact of the Lombard effect on audio and visual speech recognition systems R Marxer, J Barker, N Alghamdi, S Maddock Speech communication 100, 58-68, 2018	42	2018
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	41	2015
Automatic dysfluency detection in dysarthric speech using deep belief networks S Oue, R Marxer, F Rudzicz proceedings of SLPAT 2015: 6th workshop on speech and language processing …, 2015	38	2015
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	37	2008
The CHiME challenges: Robust speech recognition in everyday environments JP Barker, R Marxer, E Vincent, S Watanabe New era for robust speech recognition: Exploiting deep learning, 327-344, 2017	30	2017
Aligned contrastive predictive coding J Chorowski, G Ciesielski, J Dzikowski, A Łańcucki, R Marxer, M Opala, ... arXiv preprint arXiv:2104.11946, 2021	29	2021
A convolutional deep markov model for unsupervised speech representation learning S Khurana, A Laurent, WN Hsu, J Chorowski, A Lancucki, R Marxer, ... arXiv preprint arXiv:2006.02547, 2020	29	2020
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	27*	2016
Contrastive prediction strategies for unsupervised segmentation and categorization of phonemes and words S Cuervo, M Grabias, J Chorowski, G Ciesielski, A Łańcucki, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022	25	2022
Low-latency instrument separation in polyphonic audio using timbre models R Marxer, J Janer, J Bonada Latent Variable Analysis and Signal Separation: 10th International …, 2012	23	2012
DOCC10: Open access dataset of marine mammal transient studies and end-to-end CNN classification M Ferrari, H Glotin, R Marxer, M Asch 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020	21	2020

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