Comparer des méthodes

	Classification de genres musicaux	Suivi du tempo
Domaine	Recherche d'information musicale	Recherche d'information musicale
Famille	Machine learning	Machine learning
Année d'origine	2002	2007
Auteur d'origine	George Tzanetakis	David P. Ellis
Type	Audio feature-based classification	Audio signal processing algorithm
Source fondatrice	Tzanetakis, G., & Cook, P. (2002). Musical genre classification of audio signals. IEEE Transactions on Speech and Audio Processing, 10(5), 293-302.	Ellis, D. P. (2007). Beat tracking by dynamic programming. Journal of New Music Research, 36(1), 51-60.
Alias	genre recognition, music categorization, style classification	pulse detection, beat detection, metrical analysis
Apparentées	5	5
Résumé	Music genre classification is the task of automatically assigning genre labels (rock, jazz, classical, pop, etc.) to audio recordings. Introduced formally by Tzanetakis and Cook (2002), it is one of the earliest and most studied music information retrieval problems. It remains critical for music discovery, recommendation systems, digital library organization, and music streaming services. Modern systems achieve high accuracy on standard datasets using deep learning.	Beat tracking is an algorithm for automatically identifying the temporal positions of musical beats in audio recordings. It has been widely studied since the early 2000s, particularly for rhythm analysis and music synchronization applications. The problem is central to music information retrieval and essential for music-aware systems.