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Richard Vogl

Picture of Richard

DI Dr. techn. Richard Vogl
TU Wien
Faculty of Informatics
Institute of Information Systems Engineering
Information & Software Engineering Group
Favoritenstraße 9-11/194-1, 1040 Vienna, Austria

Office: Room HE 01 46
Hours: by appointment
Phone: +43 1 58801 188 309
e-mail: email adress

Short CV

Richard Vogl's research is situated at the intersection of music and artificial intelligence. He holds a PhD and masters degree in computer science with focus on machine learning, both from Johannes Kepler University (JKU), Linz. In the recent past he worked as a researcher at the Institute of Computational Perception at JKU Linz on the GiantSteps) project; as well as at the Faculty of Informatics at TU Wien on the SmarterJam project. His main interests are deep learning, signal processing, and music information research.

Publications

2019

Richard Vogl, Hamid Eghbal-zadeh, Peter Knees. An Automatic Drum Machine with Touch UI Based on a Generative Neural Network. In Demos and Posters Session of the 24th ACM Intelligent User Interfaces Conference (IUI), Los Angeles, CA, USA, 2019.
paper

2018

Richard Vogl. Deep Learning Methods for Drum Transcription and Drum Pattern Generation. Doctoral Thesis.
thesis
thesis
Richard Vogl, Gerhard Widmer, and Peter Knees. Towards Multi-Instrument Drum Transcription. In Proceedings of the 21st International Conference on Digital Audio Effects (DAFx-18), Aveiro, Portugal, 2018.
DAFx 2018 2nd Best Paper Award.
paper
slides
accompanying website
Chih-Wei Wu, Christian Dittmar, Carl Southall, Richard Vogl, Gerhard Widmer, Jason Hockman, Meinard Müller, and Alexander Lerch. A Review of Automatic Drum Transcription. In: IEEE Transactions on Audio, Speech and Language Processing, vol. 26 nr. 9, pp. 1457—1483, (2018).
article
accompanying website
Richard Vogl*, Hamid Eghbal-Zadeh*, Gerhard Widmer, Peter Knees. GANs and Poses: An Interactive Generative Music Installation Controlled by Dance Moves. Interactive Machine-Learning for Music @Exhibition at ISMIR, Paris, France, 2018.
*Equal contribution.
paper
poster
Hamid Eghbal-Zadeh*, Richard Vogl*, Gerhard Widmer, Peter Knees. A GAN based Drum Pattern Generation UI Prototype. Late Breaking/Demos, 19th International Society for Music Information Retrieval Conference (ISMIR), Paris, France, 2018.
*Equal contribution.
paper
poster
Richard Vogl and Peter Knees. MIREX Submission For Drum Transcription 2018. MIREX submission abstracts, 2018.
paper
MIREX results page
madmom package with trained models

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, China, 2017.
paper
slides
dataset
Richard Vogl, Matthias Dorfer, Gerhard Widmer, and Peter Knees. MIREX Submission for Drum Transcription 2017. MIREX submission abstracts, 2017.
paper
MIREX results page
madmom package with trained models
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.
paper
slides
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, Denmark, 2017.
paper
poster

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.
paper
poster
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.
article
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.
paper
poster

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, Spain, 2015.
paper
poster
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, Ireland, 2015.
paper
poster

Talks

2019

Christine Bauer, Peter Knees, Richard Vogl, and Hansi Raber. Recommenders and Intelligent Tools in Music Creation: Why, Why Not, and How? At the 40th Ars Electronica Festival, AIxMusic Workshop. Linz, Austria, September 2019.
slides

2018

Richard Vogl. Drum transcription via joint beat and drum modeling using convolutional recurrent neural networks. At the 21st Vienna Deep Learning Meetup. Vienna, Austria, October 2018.
slides
Richard Vogl. From Drum Transcription to Drum Pattern Generation. At the 1st Austrian Music Information Retrieval Workshop (AMIR). Vienna, Austria, June 2018.
slides

Awards

2018

Best Documentation at the HAMR hackathon 2018 in Paris, for the software hack Neural Bubble Beat, by Florian Henkel, Filip Korzeniowski, Matthias Dorfer, and Richard Vogl.
Second best paper award at the 21st International Conference on Digital Audio Effects (DAFx-18), for the paper Towards Multi-Instrument Drum Transcription, by Richard Vogl, Gerhard Widmer, and Peter Knees.

2016

Best Gesture and Sound combination at the Waves Vienna Music Hackday 2016, for the hardware hack Metal Stance, by Richard Vogl and Daniel Hütter.

2015

Best Bitalino Hack and Best Juce Hack at the Music Hack Day at Sónar 2015 in Barcelona, for the hardware hack JucyPaintAlinoBrick, by Richard Vogl and Peter Knees.
source code