- Ph.D. Candidate
- BS/MS Electrical Engineering, Drexel University 2013 (Cum Laude)
I am currently a research assistant in the Music and Entertainment Technology Laboratory (MET-lab) at Drexel University. My primary interests are in digital signal processing and machine learning, and their application to music and audio. Before joining MET-lab, I worked as a systems engineer at Custom Molders Group.
In the late summer of 2014, I received Drexel's Freshman Engineering Design Fellowship. In coordination with faculty and other Ph.D. students, I teach fundamental programming techniques to incoming engineering students.
- Machine Learning
- Digital Signal Processing
- Music Information Retrieval
Music Emotion Recognition
In developing automated systems to recognize the emotional content of music, we are faced with a problem spanning two disparate domains: the space of human emotions and the acoustic signal of music. To address this problem, we must develop models for both data collected from humans describing their perceptions of musical mood and quantitative features derived from the audio signal.
- M. Soleymani, A. Aljanaki, Y. Yang, M. Caro, F. Eyben, K. Markov, B. Schuller, R. Veltkamp, F. Weninger, F. Wiering. Emotional analysis of music: A comparison of methods. In Proceedings of the ACM International Conference on Multimedia, pages 1161-1164. ACM, 2014.
- M. Soleymani, M. Caro, E. M. Schmidt, Y. Yang. The mediaeval 2013 brave new task: Emotion in music. In MediaEval. Citeseer, 2013.
- M. Soleymani, M. Caro, E. M. Schmidt, C. Sha, Y. Yang. 1000 Songs for Emotional Analysis of Music. In Proceedings of the ACM multimedia 2013 workshop on Crowdsourcing for Multimedia, pages 1-6. ACM, 2013.