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Mark Hasegawa-Johnson
Mark Hasegawa-Johnson
Professor of Electrical and Computer Engineering, University of Illinois
Geverifieerd e-mailadres voor illinois.edu - Homepage
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Semantic image inpainting with deep generative models
RA Yeh, C Chen, T Yian Lim, AG Schwing, M Hasegawa-Johnson, MN Do
Proceedings of the IEEE conference on computer vision and pattern …, 2017
12672017
Joint optimization of masks and deep recurrent neural networks for monaural source separation
PS Huang, M Kim, M Hasegawa-Johnson, P Smaragdis
IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (12 …, 2015
5242015
Deep learning for monaural speech separation
PS Huang, M Kim, M Hasegawa-Johnson, P Smaragdis
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
5112014
Brain anatomy differences in childhood stuttering
SE Chang, KI Erickson, NG Ambrose, MA Hasegawa-Johnson, ...
Neuroimage 39 (3), 1333-1344, 2008
4552008
Singing-voice separation from monaural recordings using robust principal component analysis
PS Huang, SD Chen, P Smaragdis, M Hasegawa-Johnson
2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012
4312012
Autovc: Zero-shot voice style transfer with only autoencoder loss
K Qian, Y Zhang, S Chang, X Yang, M Hasegawa-Johnson
International Conference on Machine Learning, 5210-5219, 2019
4112019
Semantic image inpainting with perceptual and contextual losses
R Yeh, C Chen, TY Lim, M Hasegawa-Johnson, MN Do
arXiv preprint arXiv:1607.07539 2 (3), 2016
4052016
Dysarthric speech database for universal access research
H Kim, M Hasegawa-Johnson, A Perlman, J Gunderson, TS Huang, ...
Ninth Annual Conference of the International Speech Communication Association, 2008
3312008
Dilated recurrent neural networks
S Chang, Y Zhang, W Han, M Yu, X Guo, W Tan, X Cui, M Witbrock, ...
Advances in neural information processing systems 30, 2017
3152017
AVICAR: Audio-visual speech corpus in a car environment
B Lee, M Hasegawa-Johnson, C Goudeseune, S Kamdar, S Borys, M Liu, ...
Eighth International Conference on Spoken Language Processing, 2004
2392004
Signal-based and expectation-based factors in the perception of prosodic prominence
J Cole, Y Mo, M Hasegawa-Johnson
Laboratory Phonology 1 (2), 425-452, 2010
2312010
Streaming recommender systems
S Chang, Y Zhang, J Tang, D Yin, Y Chang, MA Hasegawa-Johnson, ...
Proceedings of the 26th international conference on world wide web, 381-389, 2017
2162017
Real-world acoustic event detection
X Zhuang, X Zhou, MA Hasegawa-Johnson, TS Huang
Pattern recognition letters 31 (12), 1543-1551, 2010
2152010
Regression from patch-kernel
S Yan, X Zhou, M Liu, M Hasegawa-Johnson, TS Huang
2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008
2102008
Acoustic fall detection using Gaussian mixture models and GMM supervectors
X Zhuang, J Huang, G Potamianos, M Hasegawa-Johnson
2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009
1942009
Singing-Voice Separation from Monaural Recordings using Deep Recurrent Neural Networks.
PS Huang, M Kim, M Hasegawa-Johnson, P Smaragdis
ISMIR, 477-482, 2014
1772014
Articulatory feature-based methods for acoustic and audio-visual speech recognition: Summary from the 2006 JHU summer workshop
K Livescu, O Cetin, M Hasegawa-Johnson, S King, C Bartels, N Borges, ...
2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007
1602007
Unsupervised speech decomposition via triple information bottleneck
K Qian, Y Zhang, S Chang, M Hasegawa-Johnson, D Cox
International Conference on Machine Learning, 7836-7846, 2020
1592020
Prosodic effects on acoustic cues to stop voicing and place of articulation: Evidence from Radio News speech
J Cole, H Kim, H Choi, M Hasegawa-Johnson
Journal of Phonetics 35 (2), 180-209, 2007
1552007
Sift-bag kernel for video event analysis
X Zhou, X Zhuang, S Yan, SF Chang, M Hasegawa-Johnson, TS Huang
Proceedings of the 16th ACM international conference on Multimedia, 229-238, 2008
1412008
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Artikelen 1–20