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They have, however, seldom been used in this area, so this paper explores their possible uses. This project contributes a new open source library, which was developed to allow ESNs to run in the Pure Data dataflow environment. Several use cases were explored, focusing on addressing current issues in mapping research. ESNs were found to work successfully in scenarios of pattern classification, multiparametric control, explorative mapping and the design of nonlinearities and uncontrol. \\emph{Un-trained} behaviours are proposed, as augmentations to the conventional reservoir system that allow the player to introduce potentially interesting non-linearities and uncontrol into the reservoir. Interactive evolution style controls are proposed as strategies to help design these behaviours, which are otherwise dependent on arbitrary parameters. A study on sound classification shows that ESNs can reliably differentiate between two drum sounds, and also generalise to other similar input. 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Only peer-reviewed papers accepted for and presented at the NIME conferences will be included here.
\r\n", "page": "This collection contains peer-reviewed papers published as part of the official proceedings of the International Conference on New Interfaces for Musical Expression (NIME). The NIME conference gathers researchers and musicians from all over the world to share their knowledge and late-breaking work on new musical interface design. The conference started as a workshop at the Conference on Human Factors in Computing Systems (CHI) in 2001. Since then, an annual series of international conferences have been held around the world, hosted by research groups dedicated to interface design, human-computer interaction, and computer music. There is also a separate conference archive for NIME material that is not peer-reviewed, and a community archive for anything else.
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