Improving Automatic Music Genre Classification Systems by Using Descriptive Statistical Features of Audio Signals

Author:

Perera RavinduORCID,Wickramasinghe ManjusriORCID,Jayaratne Lakshman

Publisher

Springer Nature Switzerland

Reference23 articles.

1. Jeong, Y., Lee, K.: Learning temporal features using a deep neural network and its application to music genre classification. In: 17th International Society for Music Information Retrieval Conference (ISMIR), New York (2016)

2. Scaringella, N., Zoia, G., Mlynek, D.: Automatic genre classification of music content: a survey. In: IEEE Signal Processing Magazine, vol. 22 no. 2 (2006)

3. Anan, Y., Hatano, K., Bannai, H., Takeda, M.: Music genre classification using similarity functions. In: 12th International Society for Music Information Retrieval Conference (ISMIR 2011) (2011)

4. Arora, V., Kumar, R.: Probability distribution estimation of music signals in time and frequency domains. In: 19th International Conference on Digital Signal Processing, Hong Kong (2014)

5. Corrêa, D.C., Rodrigues, F.A.: A survey on symbolic data-based music genre classification. Expert Syst. Appl. Int. J. vol. 6, no. C (2016)

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