NDLI: Music emotion recognition using PSO-based fuzzy hyper-rectangular composite neural networks

Content Provider	IET Digital Library
Author	Chin, Yu Hao Hsieh, Yi Zeng Su, Mu Chun Lee, Shu Fang Chen, Miao Wen Wang, Jia Ching
Abstract	This study proposed a novel system for recognising emotional content in music, and the proposed system is based on particle swarm optimisation (PSO)-based fuzzy hyper-rectangular composite neural networks (PFHRCNNs), which integrates three computational intelligence tools, i.e. hyper-rectangular composite neural networks (HRCNNs), fuzzy systems, and PSO. PFHRCNN is flexible to the complex data due to the fuzzy membership estimation, and an optimisation of the parameters is provided by PSO. First, raw features are extracted from each music clips. After feature extraction, a HRCNN is separately constructed for each class. Each trained HRCNN will result in a set of crisp rules. A problem associated with these generated crisp rules is that some of them are ineffective; therefore, a crisp rule is transformed into a fuzzy rule incorporated with a confidence factor. Next, PSO is adopted to simultaneously trim the rules, search a set of good confidence factors, and fine-tune the locations of the selected hyper-rectangles to increase their effectiveness. Finally, a PFHRCNN consisted of a set of fuzzy rules can be generated to recognise the emotion state of music. The experimental result shows that the proposed system has a good performance.
Starting Page	884
Ending Page	891
Page Count	8
ISSN	17519675
Volume Number	11
e-ISSN	17519683
Issue Number	Issue 7, Sep (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/11/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0021
Journal	IET Signal Processing
Publisher Date	2017-06-05
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Combinatorial Mathematics Computational Intelligence Tools Confidence Factor Emotion Recognition Emotional Content Fuzzy Hyper Rectangular Composite Neural Network Fuzzy Membership Estimation Fuzzy Set Theory Humanities Computing Music Music Emotion Recognition Neural Computing Technique Neural Nets Optimisation Technique Particle Swarm Optimisation Particle Swarm Optimisation Based Fuzzy Hyper-rectangular Composite Neural Network PFHRCNNs PSO Speech Processing Technique Speech Recognition And Synthesis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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