An audio-visual corpus for speech perception and automatic speech recognition M Cooke, J Barker, S Cunningham, X Shao The Journal of the Acoustical Society of America 120 (5), 2421-2424, 2006 | 901 | 2006 |
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 | 497 | 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 | 248 | 2017 |
The PASCAL CHiME speech separation and recognition challenge J Barker, E Vincent, N Ma, H Christensen, P Green Computer Speech & Language 27 (3), 621-633, 2013 | 246 | 2013 |
The second ‘CHiME’speech separation and recognition challenge: Datasets, tasks and baselines E Vincent, J Barker, S Watanabe, J Le Roux, F Nesta, M Matassoni 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 222 | 2013 |
The foreign language cocktail party problem: Energetic and informational masking effects in non-native speech perception M Cooke, ML Garcia Lecumberri, J Barker The Journal of the Acoustical Society of America 123 (1), 414-427, 2008 | 221 | 2008 |
Decoding speech in the presence of other sources JP Barker, MP Cooke, DPW Ellis speech communication 45 (1), 5-25, 2005 | 184 | 2005 |
The fifth'CHiME'speech separation and recognition challenge: dataset, task and baselines J Barker, S Watanabe, E Vincent, J Trmal arXiv preprint arXiv:1803.10609, 2018 | 181 | 2018 |
Soft decisions in missing data techniques for robust automatic speech recognition J Barker, L Josifovski, M Cooke, P Green Sixth International Conference on Spoken Language Processing, 2000 | 172 | 2000 |
Robust ASR based on clean speech models: An evaluation of missing data techniques for connected digit recognition in noise J Barker, M Cooke, P Green Seventh European Conference on Speech Communication and Technology, 2001 | 159 | 2001 |
The CHiME corpus: a resource and a challenge for computational hearing in multisource environments H Christensen, J Barker, N Ma, PD Green Eleventh Annual Conference of the International Speech Communication Association, 2010 | 143 | 2010 |
Modelling speaker intelligibility in noise J Barker, M Cooke Speech Communication 49 (5), 402-417, 2007 | 111 | 2007 |
The second ‘CHiME’speech separation and recognition challenge: An overview of challenge systems and outcomes E Vincent, J Barker, S Watanabe, J Le Roux, F Nesta, M Matassoni 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 162-167, 2013 | 94 | 2013 |
Mask estimation for missing data speech recognition based on statistics of binaural interaction S Harding, J Barker, GJ Brown IEEE Transactions on Audio, Speech, and Language Processing 14 (1), 58-67, 2005 | 83 | 2005 |
Techniques for handling convolutional distortion withmissing data'automatic speech recognition KJ Palomäki, GJ Brown, JP Barker Speech Communication 43 (1-2), 123-142, 2004 | 81 | 2004 |
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 | 74 | 2017 |
Exploiting correlogram structure for robust speech recognition with multiple speech sources N Ma, P Green, J Barker, A Coy Speech Communication 49 (12), 874-891, 2007 | 67 | 2007 |
Speech fragment decoding techniques for simultaneous speaker identification and speech recognition J Barker, N Ma, A Coy, M Cooke Computer Speech & Language 24 (1), 94-111, 2010 | 57 | 2010 |
Chime-home: A dataset for sound source recognition in a domestic environment P Foster, S Sigtia, S Krstulovic, J Barker, MD Plumbley 2015 IEEE Workshop on Applications of Signal Processing to Audio and …, 2015 | 56 | 2015 |
Evidence of correlation between acoustic and visual features of speech JP Barker, F Berthommier Ohala et al, 199-202, 1999 | 54 | 1999 |