SELECTED ADVANCES IN MUSIC COMPUTING FOR HUMAN HEALTH AND POTENTIAL

Abstract

Besides being an art form and serving as entertainment, music plays essential roles in many other practical applications, especially those promoting Human Health and Potential. In this thesis, we select and work on two specific applications of utilizing music computing to promote human health and potential. MusicRx-C, music generation for gait rehabilitation, belongs to music computing for enhancing human health. And AI-lyricist, lyrics generation for language learning belongs to music computing for promoting human potential. Continuing to study, we start to model users' music preferences from their listening histories. On the other hand, we improve the robustness and accuracy of identifying the main melody track of a MIDI file. This improvement allows us to perform a better alignment of lyrics syllables to melody notes. Our experiment results show the effectiveness of these two applications and the potential of music computing in promoting human health and potential.