Сравнение методов

	Сегментация музыки	Извлечение мелодии
Область	Извлечение музыкальной информации	Извлечение музыкальной информации
Семейство	Machine learning	Machine learning
Год появления	2001	2008
Автор метода	Masataka Goto	Anssi Klapuri
Тип	Audio structural analysis	Polyphonic audio analysis
Основополагающий источник	Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval.	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.
Другие названия	structural segmentation, music structure analysis, section boundary detection	pitch contour extraction, melodic line extraction, f0 tracking
Связанные	5	5
Сводка	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.	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.