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Poster communications

A neural network for composer classification

Gianluca Micchi 1, 2
2 Algomus
MIS - Modélisation, Information et Systèmes - UR UPJV 4290, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : I present a neural network approach to automatically extract musical features from 20-second audio clips in order to predict their composer. The network is composed of three convolutional layers followed by a long short-term memory recurrent layer. The model reaches an accuracy of 70% on the validation set when classifying amongst 6 composers. The work represents the early stage of a project devoted to automatic feature detection and visualization.
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Submitted on : Saturday, September 22, 2018 - 7:17:46 PM
Last modification on : Tuesday, April 27, 2021 - 3:37:45 PM
Long-term archiving on: : Sunday, December 23, 2018 - 1:12:59 PM


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  • HAL Id : hal-01879276, version 1



Gianluca Micchi. A neural network for composer classification. International Society for Music Information Retrieval Conference (ISMIR 2018), 2018, Paris, France. ⟨hal-01879276⟩



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