Bandingkan metode

	Pitch Detection Algorithm	Pelacakan Ketukan
Bidang	Temu Kembali Informasi Musik	Temu Kembali Informasi Musik
Keluarga	Machine learning	Machine learning
Tahun asal	2002	2007
Pencetus	Alain de Cheveigné	David P. Ellis
Tipe	Fundamental frequency estimation	Audio signal processing algorithm
Sumber perintis	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.
Alias	f0 detection, fundamental frequency tracking, monophonic pitch extraction	pulse detection, beat detection, metrical analysis
Terkait	5	5
Ringkasan	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.