Measuring Song Complexity by Statistical Techniques

Author:

Chakrabarty Sudipta,Banik Sangeeta,Ruhul Islam Md.,Deva Sarma Hiren Kumar

Publisher

Springer Singapore

Reference15 articles.

1. Baratè, A., Mauro, A.D., Haus, G., Ludovico, L.A.: Formalizing Schoenberg’s fundamentals of musical composition through Petri Nets. In: 15th Sound and Music Computing Conference (SMC2018), Limassol, Cyprus, pp. 254–258, 4–7 July 2018

2. Chakrabarty, S., Ruhul Islam, Md., Deva Sarma, H.K.: An approach towards the modeling of pattern similarity in music using statistical measures. Presented paper in the 5th IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC), in JUIT, Waknaghat, Himachal Pradesh, Dec 2018

3. Chakrabarty, S., Banik, S., Ruhul Islam, Md., Deva Sarma, H.K.: Context aware song recommendation system. Presented Paper in the 3rd National Conference on Communication, Cloud, and Big Data (CCB), in SMIT, Majhitar, East Sikkim, Nov 2018

4. Arutyunova, V., Averkin, A.: Genetic algorithms for music variation on genom platform. In: 9th International Conference on Theory and Application of Soft Computing, Computing with Words and Perception, ICSCCW 2017, Budapest, Hungary, 24–25 Aug 2017. Procedia Comput. Sci. 120, 317–324 (2017)

5. Chakrabarty, S., Md. Ruhul Islam, De, D.: Modelling of song pattern similarity using coefficient of variance. Int. J. Comput. Sci. Inf. Secur. 388–394 (2017). ISSN 1947-5500

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