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Stylistic Composition of Melodies Based on a Brain-Inspired Spiking Neural Network
Liang, Qian1,2; Zeng, Yi1,2,3,4
发表期刊FRONTIERS IN SYSTEMS NEUROSCIENCE
2021-03-11
卷号15期号:0页码:21
摘要

Current neural network based algorithmic composition methods are very different compared to human brain's composition process, while the biological plausibility of composition and generative models are essential for the future of Artificial Intelligence. To explore this problem, this paper presents a spiking neural network based on the inspiration from brain structures and musical information processing mechanisms at multiple scales. Unlike previous methods, our model has three novel characteristics: (1) Inspired by brain structures, multiple brain regions with different cognitive functions, including musical memory and knowledge learning, are simulated and cooperated to generate stylistic melodies. A hierarchical neural network is constructed to formulate musical knowledge. (2) Biologically plausible neural model is employed to construct the network and synaptic connections are modulated using spike-timing-dependent plasticity (STDP) learning rule. Besides, brain oscillation activities with different frequencies perform importantly during the learning and generating process. (3) Based on significant musical memory and knowledge learning, genre-based and composer-based melody composition can be achieved by different neural circuits, the experiments show that the model can compose melodies with different styles of composers or genres.

关键词spiking neural network spike-timing dependent plasticity sequential memory musical learning melody composition
DOI10.3389/fnsys.2021.639484
收录类别SCI
语种英语
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDB32070100] ; new generation of artificial intelligencemajor project of the Ministry of Science and Technology of the People's Republic of China[2020AAA0104305] ; Beijing Municipal Commission of Science and Technology[Z181100001518006] ; Key Research Program of Frontier Sciences, CAS[ZDBS-LY-JSC013] ; Beijing Academy of Artificial Intelligence (BAAI)
项目资助者Strategic Priority Research Program of the Chinese Academy of Sciences ; new generation of artificial intelligencemajor project of the Ministry of Science and Technology of the People's Republic of China ; Beijing Municipal Commission of Science and Technology ; Key Research Program of Frontier Sciences, CAS ; Beijing Academy of Artificial Intelligence (BAAI)
WOS研究方向Neurosciences & Neurology
WOS类目Neurosciences
WOS记录号WOS:000632426100001
出版者FRONTIERS MEDIA SA
七大方向——子方向分类类脑模型与计算
引用统计
被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/44001
专题脑图谱与类脑智能实验室_类脑认知计算
通讯作者Zeng, Yi
作者单位1.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China
第一作者单位类脑智能研究中心
通讯作者单位类脑智能研究中心;  模式识别国家重点实验室
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GB/T 7714
Liang, Qian,Zeng, Yi. Stylistic Composition of Melodies Based on a Brain-Inspired Spiking Neural Network[J]. FRONTIERS IN SYSTEMS NEUROSCIENCE,2021,15(0):21.
APA Liang, Qian,&Zeng, Yi.(2021).Stylistic Composition of Melodies Based on a Brain-Inspired Spiking Neural Network.FRONTIERS IN SYSTEMS NEUROSCIENCE,15(0),21.
MLA Liang, Qian,et al."Stylistic Composition of Melodies Based on a Brain-Inspired Spiking Neural Network".FRONTIERS IN SYSTEMS NEUROSCIENCE 15.0(2021):21.
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