Bandingkan kaedah

	Penjejakan Rentak	Algoritma Pengesanan Pic
Bidang	Capaian Maklumat Muzik	Capaian Maklumat Muzik
Keluarga	Machine learning	Machine learning
Tahun asal	2007	2002
Pengasas	David P. Ellis	Alain de Cheveigné
Jenis	Audio signal processing algorithm	Fundamental frequency estimation
Sumber perintis	Ellis, D. P. (2007). Beat tracking by dynamic programming. Journal of New Music Research, 36(1), 51-60.	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.
Alias	pulse detection, beat detection, metrical analysis	f0 detection, fundamental frequency tracking, monophonic pitch extraction
Berkaitan	5	5
Ringkasan	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.	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.