A learning-based jam session system that imitates a player's personality model
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Distinguishing Monophonies From Polyphonies Using Weibull Bivariate Distributions
IEEE Transactions on Audio, Speech, and Language Processing
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Loop pedals are real-time samplers that playback audio played previously by a musician. Such pedals are routinely used for music practice or outdoor "busking". However, loop pedals always playback the same material, which can make performances monotonous and boring both to the musician and the audience, preventing their widespread uptake in professional concerts. In response, we propose a new approach to loop pedals that addresses this issue, which is based on an analytical multi-modal representation of the audio input. Instead of simply playing back prerecorded audio, our system enables real-time generation of an audio accompaniment reacting to what is currently being performed by the musician. By combining different modes of performance - e.g. bass line, chords, solo - from the musician and system automatically, solo musicians can perform duets or trios with themselves, without engendering the so-called canned (boringly repetitive and unresponsive) music effect of loop pedals. We describe the technology, based on supervised classification and concatenative synthesis, and then illustrate our approach on solo performances of jazz standards by guitar. We claim this approach opens up new avenues for concert performance.