吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (3): 866-873.doi: 10.13229/j.cnki.jdxbgxb20170509

• Orginal Article • Previous Articles     Next Articles

Automatic music composition algorithm based on recurrent neural network

LI Xiong-fei1, FENG Ting-ting2, LUO Shi1, ZHANG Xiao-li1   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012,China;
    2.College of Software, Jilin University, Changchun 130012,China
  • Received:2017-05-18 Online:2018-05-20 Published:2018-05-20
  • Supported by:
     

RICH HTML

5   

PDF (PC)

464

Abstract: In this paper, we propose an automatic music composition algorithm based on Long Short Term Memory-Recurrent Neural Network (LSTM-RNN). In this algorithm, we first divide music set into set which consists sequences of unit by length, and in the preprocessing we get the Mel frequency cepstrum coefficient as the feature of audio music. Second, the proposed training samples are trained and predicted by LSTM-RNN. Finally, the generated music sequences are joined to get a new music. In order to verify the effectiveness of the algorithm, we carry out an anonymous evaluation of the original music and the music generated by the algorithm. The results show that the algorithm can work well on automatic music composition.

Key words: artificial intelligence, recurrent neural network, automatic music composition algorithm, long short term memory model

CLC Number: 

  • TP181
[1] 刘涧泉. 第三种作曲方式——论计算机音乐创作的新思维[J]. 中国音乐,2006(3):51-54.
Liu Jian-quan.The third way of composing music on the new thinking of computer music creation[J]. Chinese Music,2006(3):51-54.
[2] Turkalo D M.All music guide to electronica (book review)[J]. Library Journal, 2001,126(13):90.
[3] Hiller L A, Isaacson L M.Experimental music/composition with an electronic computer[M]. New York: McGraw,1959.
[4] Loubet E.The beginnings of electronic music in Japan, with a focus on the NHK studio: the 1970s[J]. Computer Music Journal,1998,22(1):49-55.
[5] Sigtia S, Benetos E, Boulanger-Lewandowski N, et al.A hybrid recurrent neural network for music transcription[C]∥2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),Brisbane,QLD, Australia,2015:2061-2065.
[6] Eck D, Schmidhuber J.A first look at music composition using LSTM recurrent neural networks[M]. Lugano:IDSIA USI-SUPSI Instituto Dalle Molle, 2002.
[7] Franklin J A.Recurrent neural networks for music computation[J]. Informs Journal on Computing,2006,18(3):321-338.
[8] Liu I, Ramakrishnan B. Bach in2014: music composition with recurrent neural network[J]. Eprint Arxiv, 2014.https//arxiv.org/pdf/1412.3191.pdf.
[9] Dhanalakshmi P, Palanivel S, Ramalingam V.Classification of audio signals using SVM and RBFNN[J]. Expert Systems with Applications,2009,36(3):6069-6075.
[10] Mathieu B, Essid S, Fillon T, et al.YAAFE, an easy to use and efficient audio feature extraction software[C]∥International Society for Music Information Retrieval Conference, Ismir 2010, Utrecht, Netherlands,2010:441-446.
[11] Salas H A G, Gelbukh A, Calvo H. Music composition based on linguistic approach[C]∥Advances in Artificial Intelligence,Mexican International Conference on Artificial Intelligence, Pachuca,Mexico, 2010:117-128.
[1] DONG Sa, LIU Da-you, OUYANG Ruo-chuan, ZHU Yun-gang, LI Li-na. Logistic regression classification in networked data with heterophily based on second-order Markov assumption [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1571-1577.
[2] GU Hai-jun, TIAN Ya-qian, CUI Ying. Intelligent interactive agent for home service [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1578-1585.
[3] WANG Xu, OUYANG Ji-hong, CHEN Gui-fen. Measurement of graph similarity based on vertical dimension sequence dynamic time warping method [J]. 吉林大学学报(工学版), 2018, 48(4): 1199-1205.
[4] ZHANG Hao, ZHAN Meng-ping, GUO Liu-xiang, LI Zhi, LIU Yuan-ning, ZHANG Chun-he, CHANG Hao-wu, WANG Zhi-qiang. Human exogenous plant miRNA cross-kingdom regulatory modeling based on high-throughout data [J]. 吉林大学学报(工学版), 2018, 48(4): 1206-1213.
[5] HUANG Lan, JI Lin-ying, YAO Gang, ZHAI Rui-feng, BAI Tian. Construction of disease-symptom semantic net for misdiagnosis prompt [J]. 吉林大学学报(工学版), 2018, 48(3): 859-865.
[6] LIU Jie, ZHANG Ping, GAO Wan-fu. Feature selection method based on conditional relevance [J]. 吉林大学学报(工学版), 2018, 48(3): 874-881.
[7] WANG Xu, OUYANG Ji-hong, CHEN Gui-fen. Heuristic algorithm of all common subsequences of multiple sequences for measuring multiple graphs similarity [J]. 吉林大学学报(工学版), 2018, 48(2): 526-532.
[8] YANG Xin, XIA Si-jun, LIU Dong-xue, FEI Shu-min, HU Yin-ji. Target tracking based on improved accelerated gradient under tracking-learning-detection framework [J]. 吉林大学学报(工学版), 2018, 48(2): 533-538.
[9] LIU Xue-juan, YUAN Jia-bin, XU Juan, DUAN Bo-jia. Quantum k-means algorithm [J]. 吉林大学学报(工学版), 2018, 48(2): 539-544.
[10] QU Hui-yan, ZHAO Wei, QIN Ai-hong. A fast collision detection algorithm based on optimization operator [J]. 吉林大学学报(工学版), 2017, 47(5): 1598-1603.
[11] LI Jia-fei, SUN Xiao-yu. Clustering method for uncertain data based on spectral decomposition [J]. 吉林大学学报(工学版), 2017, 47(5): 1604-1611.
[12] SHAO Ke-yong, CHEN Feng, WANG Ting-ting, WANG Ji-chi, ZHOU Li-peng. Full state based adaptive control of fractional order chaotic system without equilibrium point [J]. 吉林大学学报(工学版), 2017, 47(4): 1225-1230.
[13] WANG Sheng-sheng, WANG Chuang-feng, GU Fang-ming. Spatio-temporal reasoning for OPRA direction relation network [J]. 吉林大学学报(工学版), 2017, 47(4): 1238-1243.
[14] MA Miao, LI Yi-bin. Multi-level image sequences and convolutional neural networks based human action recognition method [J]. 吉林大学学报(工学版), 2017, 47(4): 1244-1252.
[15] ZHOU Bing-hai, PENG Tao. Optimal schedule of just-in-time part distribution for mixed-model assembly lines [J]. 吉林大学学报(工学版), 2017, 47(4): 1253-1261.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] ZHANG Lin, ZHANG Xin-jie, GUO Kong-hui, WANG Chao, LIU Yang, LIU Tao. Rolling window optimization for intelligent vehicle trajectory planning in unknown environment[J]. 吉林大学学报(工学版), 2018, 48(3): 652 -660 .
[2] ZHAO Er-hui, MA Biao, LI He-yan, DU Qiu, WU Jian-peng, MA Cheng-nan. Effect of non-uniform contact on friction characteristics of wet clutches[J]. 吉林大学学报(工学版), 2018, 48(3): 661 -669 .
[3] LI Qi-liang, CAO Guan-ning, LI Xuan, YANG Zhi-gang, ZHONG Li-yuan. Multi-parameters aerodynamic optimization of sedan[J]. 吉林大学学报(工学版), 2018, 48(3): 670 -676 .
[4] CHEN Yong-heng, LIU Xin-shan, XIONG Shuai, WANG Kun-wei, SHEN Yao, YANG Shao-hui. Variable speed limit control under snow and ice conditions for urban expressway in junction bottleneck area[J]. 吉林大学学报(工学版), 2018, 48(3): 677 -687 .
[5] LI Zhi-hui, HU Yong-li, ZHAO Yong-hua, MA Jia-lei, LI Hai-tao, ZHONG Tao, YANG Shao-hui. Locating moving pedestrian from running vehicle[J]. 吉林大学学报(工学版), 2018, 48(3): 694 -703 .
[6] SUN Bao-feng, GAO Kun, SHEN Xiu-xiu, LIANG Ting. Location model of gas station for network expansion based on capacity balance and variable coverage radius[J]. 吉林大学学报(工学版), 2018, 48(3): 704 -711 .
[7] GONG Ya-feng, SHEN Yang-fan, TAN Guo-jin, HAN Chun-peng, HE Yu-long. Unconfined compressive strength of fiber soil with different porosity[J]. 吉林大学学报(工学版), 2018, 48(3): 712 -719 .
[8] YU Liu, LIU Zhong-chang, LIU Jin-shan, LIU Jiang-wei, DU Hong-fei, CHENG Peng. Gasoline spray front droplet size characteristics[J]. 吉林大学学报(工学版), 2018, 48(3): 720 -726 .
[9] ZHONG Bing, HONG Wei, JIN Zhao-hui, SU Yan, XIE Fang-xi, ZHANG Fu-wei. Movement characteristics of hydraulic variable valve train with early intake valve closing[J]. 吉林大学学报(工学版), 2018, 48(3): 727 -734 .
[10] JIANG Tao, LIN Xue-dong, LI De-gang, GU Jing-jing. Simulation of effect of injection method in compressed natural gas direct injection(CNG-DI) engine on formation mechanism of mixed gas and combustion characteristics[J]. 吉林大学学报(工学版), 2018, 48(3): 735 -743 .
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd