A studio performance of an RNN-controlled Touch Screen Ensemble from 2017-07-03 at the University of Oslo. In this performance, a touch-screen musician improvises with a computer-controlled ensemble of three artificial performers. A recurrent neural network tracks the touch gestures of the human performer and predicts musically appropriate gestural responses for the three artificial musicians. The performances on the three 'AI' iPads are then constructed from matching snippets of previous human recordings. A plot of the whole ensemble's touch gestures are shown on the projected screen. This performance uses Metatone Classifier (https://doi.org/10.5281/zenodo.51712) to track touch gestures and Gesture-RNN (https://github.com/cpmpercussion/...
<p>A video demonstration of RoboJam, a machine-learning system for generating musical responses in a...
This repository contains recordings of performances made by Ensemble Metatone (Christina Hopgood, Yv...
In this paper we ask whether machine learning can apply to musical ensembles as well as it does to ...
A studio performance of an RNN-controlled Touch Screen Ensemble from 2017-07-03 at the University of...
We present and evaluate a novel interface for tracking ensemble performances on touch-screens. The s...
This performance was part of a series of rehearsals-as-research by Ensemble Metatone to investigate ...
For many, the pursuit and enjoyment of musical performance goes hand-in-hand with collaborative crea...
This repository contains free-improvised performances by percussion/computer group, Ensemble Metaton...
This free-improvised set of musical works was performed by Ensemble Metatone in August 2013 at the A...
In this paper we ask whether machine learning can apply to musical ensembles as well as it does to t...
This free-improvised set of musical works was performed at a research concert by Ensemble Metatone i...
RoboJam is a machine-learning system for generating music that assists users of a touchscreen music ...
This free-improvised musical work was performed by Ensemble Metatone in May 2013 at the Australian N...
This free-improvised musical work was performed by Ensemble Metatone in May 2013 at the Australian N...
This free-improvised musical work was performed by Ensemble Metatone in April 2013 at the Australian...
<p>A video demonstration of RoboJam, a machine-learning system for generating musical responses in a...
This repository contains recordings of performances made by Ensemble Metatone (Christina Hopgood, Yv...
In this paper we ask whether machine learning can apply to musical ensembles as well as it does to ...
A studio performance of an RNN-controlled Touch Screen Ensemble from 2017-07-03 at the University of...
We present and evaluate a novel interface for tracking ensemble performances on touch-screens. The s...
This performance was part of a series of rehearsals-as-research by Ensemble Metatone to investigate ...
For many, the pursuit and enjoyment of musical performance goes hand-in-hand with collaborative crea...
This repository contains free-improvised performances by percussion/computer group, Ensemble Metaton...
This free-improvised set of musical works was performed by Ensemble Metatone in August 2013 at the A...
In this paper we ask whether machine learning can apply to musical ensembles as well as it does to t...
This free-improvised set of musical works was performed at a research concert by Ensemble Metatone i...
RoboJam is a machine-learning system for generating music that assists users of a touchscreen music ...
This free-improvised musical work was performed by Ensemble Metatone in May 2013 at the Australian N...
This free-improvised musical work was performed by Ensemble Metatone in May 2013 at the Australian N...
This free-improvised musical work was performed by Ensemble Metatone in April 2013 at the Australian...
<p>A video demonstration of RoboJam, a machine-learning system for generating musical responses in a...
This repository contains recordings of performances made by Ensemble Metatone (Christina Hopgood, Yv...
In this paper we ask whether machine learning can apply to musical ensembles as well as it does to ...