Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Separace vokálů× | Sledování beatu× | |
|---|---|---|
| Obor | Vyhledávání hudebních informací | Vyhledávání hudebních informací |
| Rodina | Machine learning | Machine learning |
| Rok vzniku≠ | 2012 | 2007 |
| Tvůrce≠ | Yonggang Han | David P. Ellis |
| Typ≠ | Audio source separation | Audio signal processing algorithm |
| Původní zdroj≠ | Han, Y., Qin, Z., & Kang, Z. (2012). Singing voice separation using spectral floor filtered spectrograms. In Proceedings of the International Society for Music Information Retrieval Conference. link ↗ | Ellis, D. P. (2007). Beat tracking by dynamic programming. Journal of New Music Research, 36(1), 51-60. DOI ↗ |
| Další názvy | singing voice extraction, voice isolation, source demixing | pulse detection, beat detection, metrical analysis |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | Vocal separation is the task of isolating the singing voice from a mixed music recording, leaving the instrumental accompaniment. Introduced formally by Han et al. (2012), it is critical for music editing, remixing, karaoke generation, and music analysis. Modern deep learning approaches (Défossez et al., 2021) have achieved impressive quality, enabling practical applications in music production and streaming services. Vocal separation is a special case of source separation, where the goal is to isolate the most perceptually salient source. | 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. |
| ScholarGateDatová sada ↗ |
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