A Compact Spectrum-Assisted Human Beatboxing Reinforcement Learning Tool On Smartphone

Lui, Simon

Proceedings of the International Conference on New Interfaces for Musical Expression

Music is expressive and hard to be described by words. Learning music istherefore not a straightforward task especially for vocal music such as humanbeatboxing. People usually learn beatboxing in the traditional way of imitatingaudio sample without steps and instructions. Spectrogram contains a lot ofinformation about audio, but it is too complicated to be understood inreal-time. Reinforcement learning is a psychological method, which makes use ofreward and/or punishment as stimulus to train the decision-making process ofhuman. We propose a novel music learning approach based on the reinforcementlearning method, which makes use of compact and easy-to-read spectruminformation as visual clue to assist human beatboxing learning on smartphone.Experimental result shows that the visual information is easy to understand inreal-time, which improves the effectiveness of beatboxing self-learning.