Сравнение методов

	Извлечение мелодии	Сегментация музыки
Область	Извлечение музыкальной информации	Извлечение музыкальной информации
Семейство	Machine learning	Machine learning
Год появления	2008	2001
Автор метода	Anssi Klapuri	Masataka Goto
Тип	Polyphonic audio analysis	Audio structural analysis
Основополагающий источник	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.	Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval.
Другие названия	pitch contour extraction, melodic line extraction, f0 tracking	structural segmentation, music structure analysis, section boundary detection
Связанные	5	5
Сводка	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.	Music segmentation is the task of dividing a musical recording into distinct structural sections (e.g., verse, chorus, bridge, pre-chorus, outro). Introduced by Goto (2001), it identifies major structural boundaries and labels sections according to musical form. Segmentation is essential for music understanding, audio editing, and composition analysis. It enables higher-level tasks like cover song identification and song structure-aware music generation.