Authors:
Nadia Lachetar
1
and
Halima Bahi
2
Affiliations:
1
Skikda University, Algeria
;
2
Annaba University, Algeria
Keyword(s):
Audio indexing, Naive Bayes algorithm, Ant colony algorithm, Song categorisation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Clustering and Classification Methods
;
Computational Intelligence
;
Evolutionary Computing
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Machine Learning
;
Mining Multimedia Data
;
Soft Computing
;
Symbolic Systems
Abstract:
Instead of the expansion of the information retrieval systems, the music information retrieval domain is still an open one. One of the promising areas in this context is the audio indexing databases. This paper addresses the problem of indexing database containing songs to enable their effective exploitation. Since, we are interested with songs databases, it is necessary to exploit the specific structure of the song in with each part plays a specific role. We propose to use the title and the artist particularities (in fact each artist tends to compose or sing a specific genre of music). In this article, we present our experiments in automated song categorisation, where we suggest the use of an ant colony algorithm. A naive Bayes algorithm is used as a baseline in our tests.