Erik M. Schmidt
Erik M. Schmidt
Senior Research Scientist, Netflix
Geverifieerd e-mailadres voor netflix.com
Geciteerd door
Geciteerd door
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
1000 songs for emotional analysis of music
M Soleymani, MN Caro, EM Schmidt, CY Sha, YH Yang
Proceedings of the 2nd ACM international workshop on Crowdsourcing for …, 2013
End-to-end learning for music audio tagging at scale
J Pons, O Nieto, M Prockup, E Schmidt, A Ehmann, X Serra
arXiv preprint arXiv:1711.02520, 2017
Moodswings: A collaborative game for music mood label collection.
YE Kim, EM Schmidt, L Emelle
Ismir 8, 231-236, 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
Prediction of time-varying musical mood distributions using Kalman filtering
EM Schmidt, YE Kim
2010 Ninth International Conference on Machine Learning and Applications …, 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
Modeling Musical Emotion Dynamics with Conditional Random Fields.
EM Schmidt, YE Kim
ISMIR 11, 777-782, 2011
A Comparative Study of Collaborative vs. Traditional Musical Mood Annotation.
JA Speck, EM Schmidt, BG Morton, YE Kim
ISMIR 104, 549-554, 2011
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
Feature Learning in Dynamic Environments: Modeling the Acoustic Structure of Musical Emotion.
EM Schmidt, JJ Scott, YE Kim
ISMIR, 325-330, 2012
Improving music emotion labeling using human computation
BG Morton, JA Speck, EM Schmidt, YE Kim
Proceedings of the acm sigkdd workshop on human computation, 45-48, 2010
Modeling Genre with the Music Genome Project: Comparing Human-Labeled Attributes and Audio Features.
M Prockup, AF Ehmann, F Gouyon, EM Schmidt, O Celma, YE Kim
ISMIR, 31-37, 2015
Learning Rhythm And Melody Features With Deep Belief Networks.
EM Schmidt, YE Kim
ISMIR, 21-26, 2013
The MediaEval 2013 Brave New Task: Emotion in Music.
M Soleymani, MN Caro, EM Schmidt, YH Yang
MediaEval, 2013
Modeling Musical Rhythm at Scale with the Music Genome Project
M Prockup, AF Ehmann, F Gouyon, EM Schmidt, YE Kim
Applications of Signal Processing to Audio and Acoustics (WASPAA), 2015 IEEE …, 2015
Teaching stem concepts through music technology and dsp
YE Kim, AM Batula, R Migneco, P Richardson, B Dolhansky, D Grunberg, ...
2011 Digital Signal Processing and Signal Processing Education Meeting (DSP …, 2011
Utilizing music technology as a model for creativity development in K-12 education
D Rosen, EM Schmidt, YE Kim
Proceedings of the 9th ACM Conference on Creativity & Cognition, 341-344, 2013
Mood classification using listening data
F Korzeniowski, O Nieto, M McCallum, M Won, S Oramas, E Schmidt
arXiv preprint arXiv:2010.11512, 2020
Efficient Acoustic Feature Extraction for Music Information Retrieval Using Programmable Gate Arrays.
EM Schmidt, K West, YE Kim
ISMIR, 273-278, 2009
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