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The Cyborg Philharmonic: Synchronizing interactive musical performances between humans and machines

The Arts

The Cyborg Philharmonic: Synchronizing interactive musical performances between humans and machines

S. Chakraborty, S. Dutta, et al.

Dive into the revolutionary world of the 'Cyborg Philharmonic,' where humans and machines create music in perfect harmony! This groundbreaking research by Sutirtha Chakraborty, Sourav Dutta, and Joseph Timoney integrates advanced synchronization and deep learning models to redefine musical performances—making every note an unexpected delight!

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~3 min • Beginner • English
Abstract
Music offers a uniquely abstract way for the expression of human emotions and moods, wherein melodic harmony is achieved through a succinct blend of pitch, rhythm, tempo, texture, and other sonic qualities. The emerging field of “Robotic Musicianship” focuses on developing machine intelligence, in terms of algorithms and cognitive models, to capture the underlying principles of musical perception, composition, and performance. The capability of new-generation robots to manifest music in a human-like artistically expressive manner lies at the intersection of engineering, computers, music, and psychology; promising to offer new forms of creativity, sharing, and interpreting musical impulses. This manuscript explores how real-time collaborations between humans and machines might be achieved by the integration of technological and mathematical models from Synchronization and Learning, with precise configuration for the seamless generation of melody in tandem, towards the vision of human-robot symphonic orchestra. To explicitly capture the key ingredients of a good symphony—synchronization and anticipation—this work discusses a possible approach based on the joint strategy of: (i) Mapping—wherein mathematical models for oscillator coupling like Kuramoto could be used for establishing and maintaining synchronization, and (ii) Modelling—employing modern deep learning predictive models like Neural Network architectures to anticipate (or predict) future state changes in the sequence of music generation and pre-empt transitions in the coupled oscillator sequence. It is hoped that this discussion will foster new insights and research for better “real-time synchronized human-computer collaborative interfaces and interactions”.
Publisher
Humanities and Social Sciences Communications
Published On
Mar 17, 2021
Authors
Sutirtha Chakraborty, Sourav Dutta, Joseph Timoney
Tags
real-time collaboration
music performance
Cyborg Philharmonic
synchronization
deep learning
melody generation
predictive models
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