Compară metode

	Algoritm de Detecție a Înălțimii Tonului	Urmărirea ritmică
Domeniu	Regăsirea informației muzicale	Regăsirea informației muzicale
Familie	Machine learning	Machine learning
Anul apariției	2002	2007
Autorul original	Alain de Cheveigné	David P. Ellis
Tip	Fundamental frequency estimation	Audio signal processing algorithm
Sursa seminală	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.
Denumiri alternative	f0 detection, fundamental frequency tracking, monophonic pitch extraction	pulse detection, beat detection, metrical analysis
Înrudite	5	5
Rezumat	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.