Porovnat metody

	Rozpoznávání hudebních nástrojů	Segmentace hudby
Obor	Vyhledávání hudebních informací	Vyhledávání hudebních informací
Rodina	Machine learning	Machine learning
Rok vzniku	2005	2001
Tvůrce	Antti Eronen	Masataka Goto
Typ	Timbre-based audio classification	Audio structural analysis
Původní zdroj	Eronen, A., Peltonen, V., Tuomi, J., Klapuri, A., Fagerlund, S., Sorsa, T., & Lorho, G. (2005). Audio-based context recognition. IEEE Transactions on Audio, Speech, and Language Processing, 14(1), 321-329.	Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval.
Další názvy	instrument classification, timbre identification, instrument detection	structural segmentation, music structure analysis, section boundary detection
Příbuzné	5	5
Shrnutí	Instrument recognition is the task of automatically identifying which musical instruments are present in an audio recording. Formalized by Eronen et al. (2005), it addresses timbre—the tonal quality distinguishing one instrument from another. Instrument recognition is essential for music analysis, transcription, automatic indexing, and music education. It remains challenging in polyphonic contexts but has achieved good accuracy in solo and sparse accompaniment scenarios.	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.