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ORCIDErik M. Schmidt
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2020 – today
- 2020
[c23]Filip Korzeniowski, Oriol Nieto, Matthew C. McCallum, Minz Won, Sergio Oramas, Erik M. Schmidt:
Mood Classification Using Listening Data. ISMIR 2020: 542-549- [i2]Filip Korzeniowski, Oriol Nieto, Matthew C. McCallum, Minz Won, Sergio Oramas, Erik M. Schmidt:
Mood Classification Using Listening Data. CoRR abs/2010.11512 (2020)
2010 – 2019
- 2018
- [c22]Jordi Pons, Oriol Nieto, Matthew Prockup, Erik M. Schmidt, Andreas F. Ehmann, Xavier Serra:
End-to-end Learning for Music Audio Tagging at Scale. ISMIR 2018: 637-644 - 2017
- [i1]Jordi Pons, Oriol Nieto, Matthew Prockup, Erik M. Schmidt, Andreas F. Ehmann, Xavier Serra:
End-to-end learning for music audio tagging at scale. CoRR abs/1711.02520 (2017) - 2015
- [c21]Matthew Prockup, Andreas F. Ehmann, Fabien Gouyon, Erik M. Schmidt, Òscar Celma, Youngmoo E. Kim:
Modeling Genre with the Music Genome Project: Comparing Human-Labeled Attributes and Audio Features. ISMIR 2015: 31-37 - [c20]Matthew Prockup, Andreas F. Ehmann, Fabien Gouyon, Erik M. Schmidt, Youngmoo E. Kim
:
Modeling musical rhythmatscale with the music Genome project. WASPAA 2015: 1-5 - 2013
- [j2]Amelie Anglade, Eric Humphrey, Erik M. Schmidt, Sebastian Stober, Mohamed Sordo:
Demos and Late-Breaking Session of the Thirteenth International Society for Music Information Retrieval Conference (ISMIR 2012). Comput. Music. J. 37(2): 91-93 (2013) - [c19]David S. Rosen, Erik M. Schmidt, Youngmoo E. Kim:
Utilizing music technology as a model for creativity development in K-12 education. Creativity & Cognition 2013: 341-344 - [c18]Erik M. Schmidt, Youngmoo E. Kim:
Learning Rhythm And Melody Features With Deep Belief Networks. ISMIR 2013: 21-26 - [c17]Matthew Prockup, Erik M. Schmidt, Jeffrey J. Scott, Youngmoo E. Kim:
Toward Understanding Expressive Percussion Through Content Based Analysis. ISMIR 2013: 143-148 - [c16]Mohammad Soleymani, Michael N. Caro, Erik M. Schmidt, Yi-Hsuan Yang:
The MediaEval 2013 Brave New Task: Emotion in Music. MediaEval 2013 - [c15]Mohammad Soleymani, Michael N. Caro, Erik M. Schmidt, Cheng-Ya Sha, Yi-Hsuan Yang:
1000 songs for emotional analysis of music. CrowdMM@ACM Multimedia 2013: 1-6 - 2012
- [j1]David Grunberg, Alyssa M. Batula, Erik M. Schmidt, Youngmoo E. Kim:
Synthetic Emotions for Humanoids: Perceptual Effects of Size and Number of Robot Platforms. Int. J. Synth. Emot. 3(2): 68-83 (2012) - [c14]Erik M. Schmidt, Matthew Prockup, Jeffrey J. Scott, Brian Dolhansky, Brandon G. Morton, Youngmoo E. Kim:
Analyzing the Perceptual Salience of Audio Features for Musical Emotion Recognition. CMMR 2012: 278-300 - [c13]David Grunberg, Alyssa M. Batula, Erik M. Schmidt, Youngmoo E. Kim:
Affective gesturing with music mood recognition. Humanoids 2012: 343-348 - [c12]Erik M. Schmidt, Jeffrey J. Scott, Youngmoo E. Kim:
Feature Learning in Dynamic Environments: Modeling the Acoustic Structure of Musical Emotion. ISMIR 2012: 325-330 - 2011
- [c11]Jacquelin A. Speck, Erik M. Schmidt, Brandon G. Morton, Youngmoo E. Kim:
A Comparative Study of Collaborative vs. Traditional Musical Mood Annotation. ISMIR 2011: 549-554 - [c10]Erik M. Schmidt, Youngmoo E. Kim:
Modeling Musical Emotion Dynamics with Conditional Random Fields. ISMIR 2011: 777-782 - [c9]Erik M. Schmidt, Youngmoo E. Kim:
Learning emotion-based acoustic features with deep belief networks. WASPAA 2011: 65-68 - [c8]Erik M. Schmidt, Raymond Migneco, Jeffrey J. Scott, Youngmoo E. Kim:
Modeling musical instrument tones as dynamic textures. WASPAA 2011: 329-332 - 2010
- [c7]Brandon G. Morton, Jacquelin A. Speck, Erik M. Schmidt, Youngmoo E. Kim:
Improving music emotion labeling using human computation. HCOMP@KDD 2010: 45-48 - [c6]Erik M. Schmidt, Youngmoo E. Kim:
Prediction of Time-Varying Musical Mood Distributions Using Kalman Filtering. ICMLA 2010: 655-660 - [c5]Youngmoo E. Kim, Erik M. Schmidt, Raymond Migneco, Brandon G. Morton, Patrick Richardson, Jeffrey J. Scott, Jacquelin A. Speck, Douglas Turnbull:
State of the Art Report: Music Emotion Recognition: A State of the Art Review. ISMIR 2010: 255-266 - [c4]Erik M. Schmidt, Youngmoo E. Kim:
Prediction of Time-varying Musical Mood Distributions from Audio. ISMIR 2010: 465-470 - [c3]Erik M. Schmidt, Douglas Turnbull, Youngmoo E. Kim:
Feature selection for content-based, time-varying musical emotion regression. Multimedia Information Retrieval 2010: 267-274
2000 – 2009
- 2009
- [c2]Erik M. Schmidt, Kris West, Youngmoo E. Kim:
Efficient Acoustic Feature Extraction for Music Information Retrieval Using Programmable Gate Arrays. ISMIR 2009: 273-278 - 2008
- [c1]Youngmoo E. Kim, Erik M. Schmidt, Lloyd Emelle:
MoodSwings: A Collaborative Game for Music Mood Label Collection. ISMIR 2008: 231-236
Coauthor Index
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