Vocal Separation
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.
Kilderegistrering
Citater kopieret ordret fra metodens kilderegistrering. Ingen påstandsniveauverifikation er udledt heraf.
- 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. · URL
- Huang, P. S., Kim, M., Hasegawa-Johnson, M., & Smaragdis, P. (2015). Joint optimization of masks and deep recurrent neural networks for monaural source separation. IEEE Transactions on Audio, Speech, and Language Processing, 23(12), 2136-2147. · DOI 10.1109/taslp.2015.2468583
- Défossez, A., Usunier, N., Bottou, L., & Bach, F. (2021). Music source separation in the waveform domain. In International Conference on Learning Representations. · URL
Kuraterede påstande
Påstande gemt i bevis-loggen, hver med sin egen vurdering.
Denne visning opfinder ikke en påstandsvurdering, når loggen ingen har.
Relaterede metoder
Genereret fra metodegrafen og vist som maskinelt foreslåede relationer — ingen bevispåstand er udledt.