Comparar métodos

	Clasificación de Género Musical	Segmentación musical
Campo	Recuperación de información musical	Recuperación de información musical
Familia	Machine learning	Machine learning
Año de origen	2002	2001
Autor original	George Tzanetakis	Masataka Goto
Tipo	Audio feature-based classification	Audio structural analysis
Fuente seminal	Tzanetakis, G., & Cook, P. (2002). Musical genre classification of audio signals. IEEE Transactions on Speech and Audio Processing, 10(5), 293-302.	Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval.
Alias	genre recognition, music categorization, style classification	structural segmentation, music structure analysis, section boundary detection
Relacionados	5	5
Resumen	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.	Music segmentation is the task of dividing a musical recording into distinct structural sections (e.g., verse, chorus, bridge, pre-chorus, outro). Introduced by Goto (2001), it identifies major structural boundaries and labels sections according to musical form. Segmentation is essential for music understanding, audio editing, and composition analysis. It enables higher-level tasks like cover song identification and song structure-aware music generation.