Towards an automatic music arrangement framework using score reduction

Author:

Huang Jiun-Long1,Chiu Shih-Chuan1,Shan Man-Kwan2

Affiliation:

1. National Chiao Tung University, Taiwan, ROC

2. National Chengchi University, Taiwan, ROC

Abstract

Score reduction is a process that arranges music for a target instrument by reducing original music. In this study we present a music arrangement framework that uses score reduction to automatically arrange music for a target instrument. The original music is first analyzed to determine the type of arrangement element of each section, then the phrases are identified and each is assigned a utility according to its type of arrangement element. For a set of utility-assigned phrases, we transform the music arrangement into an optimization problem and propose a phrase selection algorithm. The music is arranged by selecting appropriate phrases satisfying the playability constraints of a target instrument. Using the proposed framework, we implement a music arrangement system for the piano. An approach similar to Turing test is used to evaluate the quality of the music arranged by our system. The experiment results show that our system is able to create viable music for the piano.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Co-creative Orchestration of Angeles with Layer Scores and Orchestration Plans;Lecture Notes in Computer Science;2024

2. Neural Band-to-Piano Score Arrangement with Stepless Difficulty Control;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

3. Methods of Automated Music Comparison Based on Multi-Objective Metrics of Network Similarity;Applied Sciences;2023-03-10

4. Difficulty-Aware Neural Band-to-Piano Score Arrangement based on Note- and Statistic-Level Criteria;ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

5. Statistical piano reduction controlling performance difficulty;APSIPA Transactions on Signal and Information Processing;2018

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