wekinator.cs.princeton.edu

sidebandchronicles.com

Anne Hege From the Waters

http://www.sidebandchronicles.com/anne-hege-from-the-waters

The notorious laptop band brings you their ongoing adventures with humans, computers, and sound:. What are the Sideband Chronicles? April 15, 2015. Larr; Michael Early. If laptop orchestras were used in ritual practice, what would that ritual be? In 2009, inspired by Maya Deren’s description of Haitian Voudoun practices in her book. Divine Horsemen: The Living Gods of Haiti,. In 2010, I composed the first version of this work and titled it,. Middle Passage: Reclaiming what is Lost. Inspired my revision t...

theoreticalplayground.co.uk

theoreticalplayground.co.uk : Blog Archive : The Wekinator

http://theoreticalplayground.co.uk/2011/06/the-wekinator

Audio, visual, code and science. By det on June 16th 2011 to software. Is a software application developed by Rebecca Fiebrink. Which uses machine learning. Principles in order to help develop interactive systems. The GUI provides the user with a way to ‘create machine learning models from scratch, without any programming’. The following diagram, sourced from the ChucK/Wekinator integration instructions. Provides an overview of the system. No comments yet. Be the first. Based on Flex theme.

everydayproportions.com

Videos

http://www.everydayproportions.com/pages/videos

Larr; alltom.com. Prototypes and goofing off over the years. Music visualization with libcinder. Over-the-top audio sampler in Processing (one of my favorite creations to date). Musically-responsive MIDI blocks in Processing. Musically-responsive MIDI helix in Processing. A spring model in Processing with audio generated by reading each row as a waveform at different speeds. An earlier prototype of the above. Went wild. As he says, it is his masterpiece. I taught my computer to respond to voice commands.

baptistecaramiaux.com

Machine Learning of Musical Gestures: A Review | Baptiste Caramiaux

http://baptistecaramiaux.com/machine-learning-of-musical-gestures

Machine Learning of Musical Gestures: A Review. The review has been built in collaboration with Atau Tanaka, and we presented it at NIME 2013:. Please feel free to send me your comments. Machine Learning (ML) is a body of statistical analysis methods that achieve tasks. Learning can be performed in several ways and depends on the data available as well as the imposed design. Classical types of learning are (non-exhaustive list): supervised, unsupervised, semisupervised. Illustration of supervised learning.

obviouslyboth.com

Videos

http://www.obviouslyboth.com/pages/videos

Larr; alltom.com. Prototypes and goofing off over the years. Music visualization with libcinder. Over-the-top audio sampler in Processing (one of my favorite creations to date). Musically-responsive MIDI blocks in Processing. Musically-responsive MIDI helix in Processing. A spring model in Processing with audio generated by reading each row as a waveform at different speeds. An earlier prototype of the above. Went wild. As he says, it is his masterpiece. I taught my computer to respond to voice commands.

writeloudly.com

Videos

http://www.writeloudly.com/pages/videos

Larr; alltom.com. Prototypes and goofing off over the years. Music visualization with libcinder. Over-the-top audio sampler in Processing (one of my favorite creations to date). Musically-responsive MIDI blocks in Processing. Musically-responsive MIDI helix in Processing. A spring model in Processing with audio generated by reading each row as a waveform at different speeds. An earlier prototype of the above. Went wild. As he says, it is his masterpiece. I taught my computer to respond to voice commands.

littlecode.org

Videos

http://www.littlecode.org/pages/videos

Larr; alltom.com. Prototypes and goofing off over the years. Music visualization with libcinder. Over-the-top audio sampler in Processing (one of my favorite creations to date). Musically-responsive MIDI blocks in Processing. Musically-responsive MIDI helix in Processing. A spring model in Processing with audio generated by reading each row as a waveform at different speeds. An earlier prototype of the above. Went wild. As he says, it is his masterpiece. I taught my computer to respond to voice commands.

soundlab.cs.princeton.edu

Princeton Sound Lab - [publications]

http://soundlab.cs.princeton.edu/publications

M Hoffman, D. Blei, P. Cook, "Bayesian Nonparametric Matrix Factorization for Recorded Music,". In Proceedings of the 27th International Conference on Machine Learning,. Fiebrink, R. 2010. “Real-time interaction with supervised learning.”. ACM CHI Extended Abstracts. Atlanta, April 10–15. (CHI doctoral consortium participant with published abstract). Proceedings of the International Computer Music Conference (ICMC). New York City, June 1–5. In Proceedings of ACM CHI. Pittsburgh, PA, USA, 2009. In Proceed...

craptapular.com

Videos

http://www.craptapular.com/pages/videos

Larr; alltom.com. Prototypes and goofing off over the years. Music visualization with libcinder. Over-the-top audio sampler in Processing (one of my favorite creations to date). Musically-responsive MIDI blocks in Processing. Musically-responsive MIDI helix in Processing. A spring model in Processing with audio generated by reading each row as a waveform at different speeds. An earlier prototype of the above. Went wild. As he says, it is his masterpiece. I taught my computer to respond to voice commands.

alltom.com

Videos

http://alltom.com/pages/videos

Larr; alltom.com. Prototypes and goofing off over the years. Music visualization with libcinder. Over-the-top audio sampler in Processing (one of my favorite creations to date). Musically-responsive MIDI blocks in Processing. Musically-responsive MIDI helix in Processing. A spring model in Processing with audio generated by reading each row as a waveform at different speeds. An earlier prototype of the above. Went wild. As he says, it is his masterpiece. I taught my computer to respond to voice commands.