Compara mètodes

	Algorisme de detecció de to	Beat Tracking
Camp	Recuperació d'informació musical	Recuperació d'informació musical
Família	Machine learning	Machine learning
Any d'origen	2002	2007
Autor original	Alain de Cheveigné	David P. Ellis
Tipus	Fundamental frequency estimation	Audio signal processing algorithm
Font seminal	de Cheveigné, A., & Kawahara, H. (2002). YIN, a fundamental frequency estimator for speech and music. The Journal of the Acoustical Society of America, 111(4), 1917-1930.	Ellis, D. P. (2007). Beat tracking by dynamic programming. Journal of New Music Research, 36(1), 51-60.
Àlies	f0 detection, fundamental frequency tracking, monophonic pitch extraction	pulse detection, beat detection, metrical analysis
Relacionats	5	5
Resum	Pitch detection (or fundamental frequency estimation) is the task of automatically determining the perceived pitch of a monophonic (single-source) audio signal at each moment in time. Formalized by de Cheveigné and Kawahara (2002) through the YIN algorithm, it is foundational to music and speech processing. Pitch detection enables vocal analysis, music transcription, instrument tuning, and speech analysis. Monophonic pitch is unambiguous; polyphonic pitch detection is fundamentally harder and a distinct problem.	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.