Comparative analysis of supervised classifiers for classification of musical notes on mobile based applications

Giuseppe Marotta Portal, Alberto Gonzáles Ghersi, Pedro Shiguihara Juárez, Ricardo Gonzáles Valenzuela

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Most of the work done in the field of Optical Music Recognition (OMR) is based on perfectly digitalized music scores or hand written ones as input for various algorithms developed with the goal to translate them into a language a machine can understand. However, when it comes to a mobile environment, external factors such as exposure to the elements play a huge role in the acquisition of the images. The preprocessing stage requires more attention in order to prepare the images to be classified and the classification stage has to take as little time as possible without affecting the results since we aren't working with desktop grade processing speeds. This work presents a comparative analysis between Support Vector Machine (SVM), Sequential Minimal Optimization for SVM (SMO), Multilayer Perceptron (MLP), Random Trees and Naive Bayes algorithms in the classification of whole notes, half notes, quarter notes and eight notes. This analysis is focused on the accuracy and time required to train the dataset for each classifier.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018
EditorialAssociation for Computing Machinery
ISBN (versión digital)9781450365291
DOI
EstadoPublicada - 27 ago 2018
Publicado de forma externa
Evento2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018 - Las Vegas, Estados Unidos
Duración: 27 ago 201829 ago 2018

Serie de la publicación

NombreACM International Conference Proceeding Series

Conferencia

Conferencia2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018
País/TerritorioEstados Unidos
CiudadLas Vegas
Período27/08/1829/08/18

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