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At turns lively and yearning, the traditional folk musics of Ireland and Britain have made their mark around the world. Now these perennially popular forms of music are helping computers learn to become a new kind of partner in music creation.
A machine learning system overseen by a researcher in Sweden has produced 100,000 new folk tunes to date, generating a diverse range of reactions from folk musicians and the public. Some of the music can even be heard on a newly-released album by an Irish folk group.
Bob - Sturm - Associate - Professor - Computer
Bob Sturm, associate professor of computer science at KTH Royal Institute of Technology, says that the main idea of the project was to train computer models on folk music, so that they appear to have some musical intelligence, and then to "devise methods to unravel what they are actually doing," he says.
The research subsequently led to creative opportunities.
Work - Collaborators - Composer - Ben-Tal - Kingston
"Our work with many collaborators, such as composer Oded Ben-Tal at Kingston University in the UK, and professional musicians, has also shown how the models can serve a wider purpose: as useful partners in creating new music," Sturm says.
The project uses an off-the-shelf artificial intelligence method called a recurrent neural network (RNN), which essentially predicts what comes next based on what it has previously seen. For training data, the team drew upon the website thesession.org, which contains tens-of-thousands of tunes transcribed by people using a short-hand language designed for folk music.
Computer - Models - Ability - Patterns - Ways
"The resulting computer models show some ability to repeat and vary patterns in ways that are characteristic of this kind of music," Sturm says. "It was not programmed to do this using rules – it learned to do so because these patterns exist in the data we fed it."
To test the plausibility of the generated tunes, Sturm and Ben-Tal challenged a group of professional Irish traditional musicians...
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