TY - JOUR
T1 - Development of an automatic emotional music accompaniment system by fuzzy logic and adaptive partition evolutionary genetic algorithm
AU - Kuo, Ping Huan
AU - Li, Tzuu Hseng S.
AU - Ho, Ya Fang
AU - Lin, Chih Jui
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - Music is everywhere in the world, and its applications in commerce are extremely versatile. Generally speaking, in order to create some music for background music, it is necessary to engage sound recordists and instrumental performers. However, the process is very time-consuming and costly. In this paper, a real-time emotion-based music accompaniment system is proposed to solve this issue. For different emotions, a fuzzy logic controller is designed to adjust the tempo of the music, and an adaptive partition evolutionary genetic algorithm is developed to create corresponding melodies. The chord progressions are generated via music theory, and the instrumentation is disposed by the conception of the probability. What is noteworthy is that all the processes can be output by Virtual Studio Technology in real time so that users can listen directly to the composing results from any emotions. From the experimental results, the proposed adaptive partition evolutionary genetic algorithm performs better than other optimal algorithms in such topics.
AB - Music is everywhere in the world, and its applications in commerce are extremely versatile. Generally speaking, in order to create some music for background music, it is necessary to engage sound recordists and instrumental performers. However, the process is very time-consuming and costly. In this paper, a real-time emotion-based music accompaniment system is proposed to solve this issue. For different emotions, a fuzzy logic controller is designed to adjust the tempo of the music, and an adaptive partition evolutionary genetic algorithm is developed to create corresponding melodies. The chord progressions are generated via music theory, and the instrumentation is disposed by the conception of the probability. What is noteworthy is that all the processes can be output by Virtual Studio Technology in real time so that users can listen directly to the composing results from any emotions. From the experimental results, the proposed adaptive partition evolutionary genetic algorithm performs better than other optimal algorithms in such topics.
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U2 - 10.1109/ACCESS.2015.2443985
DO - 10.1109/ACCESS.2015.2443985
M3 - Article
AN - SCOPUS:84959858823
SN - 2169-3536
VL - 3
SP - 815
EP - 824
JO - IEEE Access
JF - IEEE Access
M1 - 7122217
ER -