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Youngmoo Kim
Youngmoo Kim
Professor of Electrical and Computer Engineering, Drexel University
Verified email at drexel.edu - Homepage
Title
Cited by
Cited by
Year
Music emotion recognition: A state of the art review
YE Kim, EM Schmidt, R Migneco, BG Morton, P Richardson, J Scott, ...
Proc. ismir 86, 937-952, 2010
6222010
Singer identification in popular music recordings using voice coding features
YE Kim, B Whitman
Proceedings of the 3rd international conference on music information …, 2002
2462002
Musical instrument identification: A pattern‐recognition approach
KD Martin, YE Kim
The Journal of the Acoustical Society of America 104 (3), 1768-1768, 1998
2401998
Moodswings: A collaborative game for music mood label collection.
YE Kim, EM Schmidt, L Emelle
Ismir 8, 231-236, 2008
1552008
Comparison of brain activation during motor imagery and motor movement using fNIRS
AM Batula, JA Mark, YE Kim, H Ayaz
Computational intelligence and neuroscience 2017, 2017
1402017
Feature selection for content-based, time-varying musical emotion regression
EM Schmidt, D Turnbull, YE Kim
Proceedings of the international conference on Multimedia information …, 2010
1372010
Exploring automatic music annotation with" acoustically-objective" tags
D Tingle, YE Kim, D Turnbull
Proceedings of the international conference on Multimedia information …, 2010
1262010
Prediction of time-varying musical mood distributions using Kalman filtering
EM Schmidt, YE Kim
2010 Ninth International Conference on Machine Learning and Applications …, 2010
1242010
Prediction of time-varying musical mood distributions using Kalman filtering
EM Schmidt, YE Kim
2010 Ninth International Conference on Machine Learning and Applications …, 2010
1242010
Modeling Musical Emotion Dynamics with Conditional Random Fields.
EM Schmidt, YE Kim
ISMIR, 777-782, 2011
1072011
Learning emotion-based acoustic features with deep belief networks
EM Schmidt, YE Kim
2011 IEEE workshop on applications of signal processing to audio and …, 2011
1062011
Analysis of a Contour-based Representation for Melody.
YE Kim, W Chai, R Garcia, B Vercoe
ISMIR, 2000
882000
A Comparative Study of Collaborative vs. Traditional Musical Mood Annotation.
JA Speck, EM Schmidt, BG Morton, YE Kim
ISMIR 104, 549-554, 2011
852011
Anodal tDCS to right dorsolateral prefrontal cortex facilitates performance for novice jazz improvisers but hinders experts
DS Rosen, B Erickson, YE Kim, D Mirman, RH Hamilton, J Kounios
Frontiers in Human Neuroscience 10, 579, 2016
642016
Augmenting the Acoustic Piano with Electromagnetic String Actuation and Continuous Key Position Sensing.
AP McPherson, YE Kim
NIME, 217-222, 2010
642010
The problem of the second performer: Building a community around an augmented piano
A P. McPherson, Y E. Kim
Computer Music Journal 36 (4), 10-27, 2012
632012
Blind channel identification for speech dereverberation using l1-norm sparse learning
Y Lin, J Chen, Y Kim, D Lee
Advances in Neural Information Processing Systems 20, 2007
622007
Towards Quantifying the" Album Effect" in Artist Identification.
YE Kim, DS Williamson, S Pilli
ISMIR, 393-394, 2006
592006
Singing voice analysis/synthesis
YE Kim
Massachusetts institute of Technology, 2003
502003
Feature Learning in Dynamic Environments: Modeling the Acoustic Structure of Musical Emotion.
EM Schmidt, JJ Scott, YE Kim
ISMIR, 325-330, 2012
472012
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