Richard Vogl

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Short CV

Richard Vogl has a masters degree in computer science with focus on machine learning and is a PhD candidate with Gerhard Widmer at the Department of Computational Perception at Johannes Kepler University, Linz. He is currently working on the "SmarterJam" project with Peter Knees at the Institute of Software Technology and Interactive Systems at Vienna University of Technology. His main research interest are signal processing, deep learning, and music information retrieval.

Publications

2017

Richard Vogl, Matthias Dorfer, Gerhard Widmer, and Peter Knees. Drum transcription via joint beat and drum modeling using convolutional recurrent neural networks. In Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR), Suzhou, CN, 2018.
Richard Vogl, Matthias Dorfer, Gerhard Widmer, and Peter Knees. MIREX Submission for Drum Transcription 2017. MIREX submission abstracts, 2017.
Richard Vogl, Matthias Dorfer, and Peter Knees. Drum Transcription from Polyphonic Music with Recurrent Neural Networks. In Proceedings of the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA, 2017.
Richard Vogl, and Peter Knees. An Intelligent Drum Machine for Electronic Dance Music Production and Performance. In Proceedings of The International Conference on New Interfaces for Musical Expression (NIME), Copenhagen, DK, 2017.

2016

Richard Vogl, Matthias Dorfer, and Peter Knees. Recurrent neural networks for drum transcription In Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR), New York, NY, USA, 2016.
Richard Vogl, Matthias Leimeister, Cárthach Ó Nuanáin, Sergi Jordà, Michael Hlatky, and Peter Knees. An Intelligent Interface for Drum Pattern Variation and Comparative Evaluation of Algorithms. In Journal of the Audio Engineering Society (JAES), Volume 64 Number 7/8, July/August,2016.
Richard Vogl, and Peter Knees. An Intelligent Musical Rhythm Variation Interface. In Demos and Posters Session of the 21st ACM Intelligent User Interfaces Conference (IUI), Sonoma, CA, USA, 2016.

2015

Peter Knees, Ángel Faraldo, Perfecto Herrera, Richard Vogl, Sebastian Böck, Florian Hörschläger, Mickael Le Goff. Two Data Sets For Tempo Estimation And Key Detection In Electronic Dance Music Annotated From User Corrections. In Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR), Málaga, ES, 2015.
Florian Hörschläger, Richard Vogl, Sebastian Böck, and Peter Knees. Addressing Tempo Estimation Octave Errors in Electronic Music by Incorporating Style Information Extracted from Wikipedia. In Proceedings of the 12th Sound and Music Computing Conference (SMC), Maynooth, IR, 2015.

2014