| 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 | 670 | 2010 |
| 2pMU9. Musical instrument identification: A pattern-recognition approach KD Martin, YE Kim Presented at the 136th meeting of the Acoustical Society of America, 1998 | 267 | 1998 |
| Singer identification in popular music recordings using voice coding features YE Kim, B Whitman Proceedings of the 3rd international conference on music information …, 2002 | 251 | 2002 |
| 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 (1), 5491296, 2017 | 167 | 2017 |
| Moodswings: A collaborative game for music mood label collection. YE Kim, EM Schmidt, L Emelle Ismir 8, 231-236, 2008 | 160 | 2008 |
| 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 | 144 | 2010 |
| Prediction of time-varying musical mood distributions using Kalman filtering EM Schmidt, YE Kim 2010 Ninth International Conference on Machine Learning and Applications …, 2010 | 129 | 2010 |
| Exploring automatic music annotation with" acoustically-objective" tags D Tingle, YE Kim, D Turnbull Proceedings of the international conference on Multimedia information …, 2010 | 126 | 2010 |
| 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 | 112 | 2011 |
| Modeling Musical Emotion Dynamics with Conditional Random Fields. EM Schmidt, YE Kim ISMIR 11, 777-782, 2011 | 111 | 2011 |
| A Comparative Study of Collaborative vs. Traditional Musical Mood Annotation. JA Speck, EM Schmidt, BG Morton, YE Kim ISMIR 104, 549-554, 2011 | 90 | 2011 |
| Analysis of a Contour-based Representation for Melody. YE Kim, W Chai, R Garcia, B Vercoe ISMIR, 2000 | 89 | 2000 |
| 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 | 69 | 2016 |
| 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 | 67 | 2012 |
| Augmenting the Acoustic Piano with Electromagnetic String Actuation and Continuous Key Position Sensing. AP McPherson, YE Kim NIME, 217-222, 2010 | 62 | 2010 |
| 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 | 60 | 2007 |
| Towards Quantifying the" Album Effect" in Artist Identification. YE Kim, DS Williamson, S Pilli ISMIR, 393-394, 2006 | 60 | 2006 |
| Automatic multi-track mixing using linear dynamical systems J Scott, M Prockup, EM Schmidt, YE Kim Proceedings of the 8th Sound and Music Computing Conference, Padova, Italy, 12, 2011 | 51 | 2011 |
| Singing voice analysis/synthesis YE Kim Massachusetts institute of Technology, 2003 | 49 | 2003 |
| Feature Learning in Dynamic Environments: Modeling the Acoustic Structure of Musical Emotion. EM Schmidt, JJ Scott, YE Kim ISMIR, 325-330, 2012 | 46 | 2012 |
Erik M. SchmidtSenior Research Scientist, Netflix在 netflix.com 的电子邮件经过验证
