Towards the use of similarity distances to music genre classification: A comparative study

Abstract

Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets –or clusters– and then generating in an automatic way a new song which is somehow “inspired” in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is.

Arabic Music Analysis Using Artificial Intelligent Teqniques

“…Many different classifiers and feature extraction algorithms are utilised for automatic MGC. Gaussian mixture model (GMM) [14], radial basis function (RBF) [15], AdaBoost [16], and semi-supervised method [17] are the classifiers.…”

Mineração de dados aplicada à classificação automática de gêneros musicais

“…Diante do desempenho em alguns cenários envolvendo gêneros como o Samba, a MPB e o Rock, nota-se elementos em aberto no que condiz com a criação de limites entre determinados gêneros musicais (Goienetxea et al, 2018), uma vez que estes podem apresentar fronteiras amplas e nebulosas, representadas por características culturais (McKay and Fujinaga, 2006). Com relação aos gêneros Samba e MPB, veri cou-se uma "di culdade" em diferenciá-los durante os experimentos.…”

Feature Selection for Musical Genre Classification Using a Genetic Algorithm

“…These developments have increased research interest in music information retrieval (MIR), a field of automatic music management including music recommendation [1], music mood classification [2], and musical instrument classification [3]. As musical genres are most commonly used to manage music databases, a previous study investigated the extraction of audio features and techniques for classifying musical genres [4,5,6,7]. However, genre classification has remained a challenge [8,9], as it requires systems that are capable of performing automatic grouping [10] and querying retrieving data from large a music data set [8].…”