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Articles

PLXTRM: Prediction-Led eXtended-guitar Tool for Real-time Music applications and live performance

, , , &
Pages 187-200 | Received 22 Jun 2016, Accepted 11 Jan 2017, Published online: 13 Feb 2017
 

Abstract

This article presents PLXTRM, a system tracking picking-hand micro-gestures for real-time music applications and live performance. PLXTRM taps into the existing gesture vocabulary of the guitar player. On the first level, PLXTRM provides a continuous controller that doesn’t require the musician to learn and integrate extrinsic gestures, avoiding additional cognitive load. Beyond the possible musical applications using this continuous control, the second aim is to harness PLXTRM’s predictive power. Using a reservoir network, string onsets are predicted within a certain time frame, based on the spatial trajectory of the guitar pick. In this time frame, manipulations to the audio signal can be introduced, prior to the string actually sounding, ’prefacing’ note onsets. Thirdly, PLXTRM facilitates the distinction of playing features such as up-strokes vs. down-strokes, string selections and the continuous velocity of gestures, and thereby explores new expressive possibilities.

Acknowledgements

The authors would like to thank Johannes Taelman for providing technical support to this project. Taelman is an independent developer and creator of the Axoloti board and community: http://www.axoloti.com/.

Notes

4 Axoloti is a platform that blends sketching of digital audio algorithms with the musical playability of standalone hardware. It is an open source project by an independent Belgian developer. See Section 4.5.

Additional information

Funding

PLXTRM has a patent pending with the European Patent Office under the [submission number EP16166103.8]. The research leading to these results has received funding from the Agency for Innovation by Science and Technology in Flanders (IWT) and a Methusalem grant from the Flemish Government.

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