Salīdzināt metodes

	Melodijas ekstrakcija	Harmoniskā analīze mūzikā
Nozare	Mūzikas informācijas izgūšana	Mūzikas informācijas izgūšana
Saime	Machine learning	Machine learning
Izcelsmes gads	2008	2002
Autors	Anssi Klapuri	Bryan Pardo
Tips	Polyphonic audio analysis	Harmonic function and progression analysis
Pirmavots	Salamon, J., & Gómez, E. (2014). Melody extraction from polyphonic music signals using pitch contour characteristics. IEEE Transactions on Audio, Speech, and Language Processing, 20(6), 1759-1770.	Pardo, B., & Birmingham, W. P. (2002). Algorithms for chordal analysis. Computer Music Journal, 26(4), 27-49.
Citi nosaukumi	pitch contour extraction, melodic line extraction, f0 tracking	functional harmony analysis, harmonic progression detection, tonal function estimation
Saistītās	5	5
Kopsavilkums	Melody extraction is the task of automatically isolating the main melodic contour from polyphonic music recordings. It originated from music transcription research in the 2000s and addresses the core challenge of human pitch perception: identifying the perceptually dominant pitch when many instruments play simultaneously. Modern approaches use deep learning and are essential for music analysis, cover song detection, and music-to-lyrics alignment.	Harmonic analysis is the computational study of chord progressions, harmonic function, and tonal relationships in music. Formalized for audio by Pardo and Birmingham (2002), it goes beyond simple chord identification to interpret harmonic role and structure. Harmonic analysis is essential for music theory education, compositional understanding, and music generation systems. It requires understanding both the chords themselves and their functional relationships within a tonal context.