مقایسهٔ روش‌ها

	ردیابی ضرب (Beat Tracking)	بازشناسی آکورد	بخش‌بندی موسیقی
حوزه	بازیابی اطلاعات موسیقی	بازیابی اطلاعات موسیقی	بازیابی اطلاعات موسیقی
خانواده	Machine learning	Machine learning	Machine learning
سال پیدایش	2007	2005	2001
پدیدآور	David P. Ellis	Christopher Harte	Masataka Goto
نوع	Audio signal processing algorithm	Harmonic audio analysis	Audio structural analysis
منبع بنیادین	Ellis, D. P. (2007). Beat tracking by dynamic programming. Journal of New Music Research, 36(1), 51-60.	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.	Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval.
نام‌های دیگر	pulse detection, beat detection, metrical analysis	chord estimation, harmonic analysis, chord detection	structural segmentation, music structure analysis, section boundary detection
مرتبط	5	5	5
خلاصه	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.	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.	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.