Composer Classification Using Maximum Probability Partitioning Based on Compression Principles

Author:

Takamoto Ayaka1,Hironaka Shiori2,Umemura Kyoji1

Affiliation:

1. Department of Computer Science and Engineering, Toyohashi University of Technology

2. Academic Center for Computing and Media Studies, Kyoto University

Publisher

Japanese Society for Artificial Intelligence

Reference26 articles.

1. [足達13] 足達花絵, 岡部正幸, 梅村恭司:楽曲判定における和音の転回情報の効果, 研究報告音楽情報科学(MUS), Vol. 2013-MUS-101, No. 5 (2013)

2. [Anan 12] Anan, Y., Hatano, K., Bannai, H., Takeda, M., and Sato, K.: Polypohic music classification on symbol data using dissimilarity functions, in International Society for Music Information Retrieval Conference (2012)

3. [Cataltepe 05] Cataltepe, Z., Sonmez, A., and Adali, E.: Music classification using Kolmogorov distance, in Representation in Music/ Musical Representation Congress (2005)

4. [Cilibrasi 04] Cilibrasi, R., Vit´anyi, P., and De Wolf, R.: Algorithmic clustering of music based on string compression, Computer Music Journal, Vol. 28, No. 4, pp. 49–67 (2004)

5. [Deepaisarn 23] Deepaisarn, S., Chokphantavee, S., Chokphantavee, S., Prathipasen, P., Buaruk, S., and Sornlertlamvanich, V.: NLP-based music processing for composer classification, ScientificReports, Vol. 13, No. 1, p. 13228 (2023)

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