A neural network for composer classification - Archive ouverte HAL
Poster Communications Year : 2018

A neural network for composer classification

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.
Fichier principal
Vignette du fichier
2018-ismir-lb-composer.pdf (393.02 Ko) Télécharger le fichier
Origin Publisher files allowed on an open archive
Loading...

Dates and versions

hal-01879276 , version 1 (22-09-2018)

Licence

Identifiers

  • HAL Id : hal-01879276 , version 1

Cite

Gianluca Micchi. A neural network for composer classification. International Society for Music Information Retrieval Conference (ISMIR 2018), 2018, Paris, France. ⟨hal-01879276⟩
447 View
1241 Download

Share

More