Compară metode

	Segmentare muzicală	Recunoașterea acordurilor
Domeniu	Regăsirea informației muzicale	Regăsirea informației muzicale
Familie	Machine learning	Machine learning
Anul apariției	2001	2005
Autorul original	Masataka Goto	Christopher Harte
Tip	Audio structural analysis	Harmonic audio analysis
Sursa seminală	Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval.	Harte, C., Sandler, M. B., Abdallah, S. A., & Gómez, E. (2005). Symbolic representation of musical chords: Proposed extensions to the HarmO ontology. In Proceedings of the International Society for Music Information Retrieval Conference.
Denumiri alternative	structural segmentation, music structure analysis, section boundary detection	chord estimation, harmonic analysis, chord detection
Înrudite	5	5
Rezumat	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.	Chord recognition is the task of automatically identifying the harmonic chords present in a musical recording and estimating when chord changes occur. Introduced formally by Harte et al. (2005), it is a cornerstone of music analysis and widely used in music education, cover song analysis, and musical structure understanding. Modern systems use deep learning to classify and sequence chords in real time.