Author: Hu, Ruijie
Title: Computational approach of music quality improvement for algorithmic composition
Advisors: Liu, Yan (COMP)
Degree: M.Sc.
Year: 2019
Subject: Hong Kong Polytechnic University -- Dissertations
Computer composition (Music)
Composition (Music)
Music theory -- Mathematics
Department: Department of Computing
Pages: vi, 55 pages : color illustrations
Language: English
Abstract: Music processing is quite a new topic especially for algorithmic composition, which requires both computational skills and music theory basis. And because music is kind of art which did not exist in the nature originally, it requires subjective feeling and experience to process and produce. Through the production of MIDI based music files by Python MIDI processing, in this research, the author devotes to explore the computational rules of music and improve the quality of music according to arrangements and post processing. All the work is done by computer which implements the whole process of music production including composing, recording and mixing. The innovative feature of this research is that the author as a music composer, has essential understanding and creation in the music area. To combine with programming work, some subjective tonality and chord feature analysis based on the author's own composing experience are presented in the arrangement perspective. Through the study, some improvements for algorithmic composition in three music styles are presented, which includes Blues, Chinese style and Punk rock. Moreover, followed with the post processing method using Dynamic Audio Workstation (DAW) like Cubase, some effects and audio plug-ins are used such as Virtual Studio Technology (VST), compressor, reverberation and equalizer. Finally, there are some signal analysis by MATLAB for the processing result. They are also estimated by the survey focuses on subjective listening feel of respondents. And some algorithmic compositions eventually come up with characteristics of tonality and harmonic structure, which could be the reference to the music quality improvement for algorithmic composition.
Rights: All rights reserved
Access: restricted access

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