End-to-end music emotion variation detection using iteratively reconstructed deep features

Author:

Orjesek Richard,Jarina RomanORCID,Chmulik Michal

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference41 articles.

1. Aljanaki A, Yang Y-H, Soleymani M (2017) (2017) Developing a benchmark for emotional analysis of music. PLoS ONE 12(3):1–22

2. Amiriparian S, Gerczuk M, Coutinho E, Baird A, Ottl S, Milling M, Schuller B (2019) Emotion and themes recognition in music utilising convolutional and recurrent neural networks. In: Proc. MediaEval 2019 workshop, Sophia Antipolis, France,

3. Bai J, Peng J, Shi J, Tang D, Wu Y, Li J, Luo K (2016) Dimensional music emotion recognition by valence-arousal regression. In: IEEE 15th international conference on cognitive informatics and cognitive computing. pp 42–49

4. Barthet M, Fazekas G, Sandler M (2012) Music emotion recognition: From content-to context-based models. International symposium on computer music modeling and retrieval. Springer, Berlin, pp 228–252

5. Casey MA, Veltkamp R, Goto M, Leman M, Rhodes C, Slaney M (2008) Content-based music information retrieval: Current directions and future challenges. Proc. of the IEEE 96(4):668–696

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