Development of music emotion classification system using convolution neural network-Reference-Cited by-同舟云学术

Development of music emotion classification system using convolution neural network

Published:2020-11-26 Issue:3 Volume:24 Page:571-580
ISSN:1381-2416
Container-title:International Journal of Speech Technology
language:en
Short-container-title:Int J Speech Technol

Author:

Chaudhary Deepti^ORCID,Singh Niraj Pratap,Singh Sachin

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Link

https://link.springer.com/content/pdf/10.1007/s10772-020-09781-0.pdf

Reference46 articles.

1. Aljanaki, A. (2016). Emotion in music: Representation and computational modeling.

2. Bhattarai, B., & Lee, J. (2019). Automatic music mood detection using transfer learning and multilayer perceptron. International Journal of Fuzzy Logic and Intelligent Systems, 19(2), 88–96.

3. Bilal Er, M., & Aydilek, I. B. (2019). Music emotion recognition by using chroma spectrogram and deep visual features. Journal of Computational Intelligent Systems, 12(2), 1622–1634.

4. Bischke, B., Helber, P., Schulze, C., Srinivasan, V., Dengel, A., & Borth, D. (2017). The multimedia satellite task at mediaeval 2017: Emergency response for flooding events. In CEUR workshop proceedings, September 13–15, 2017, Ireland, Dublin.

5. Bishop, C. M. (2006). Pattern recognition and machine learning. New York: Springer.

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