Сравнение методов

	Классификация музыкальных жанров	Отслеживание тактов
Область	Извлечение музыкальной информации	Извлечение музыкальной информации
Семейство	Machine learning	Machine learning
Год появления	2002	2007
Автор метода	George Tzanetakis	David P. Ellis
Тип	Audio feature-based classification	Audio signal processing algorithm
Основополагающий источник	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.
Другие названия	genre recognition, music categorization, style classification	pulse detection, beat detection, metrical analysis
Связанные	5	5
Сводка	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.