Music Genre Classification
Music genre classification is the task of automatically assigning genre labels (rock, jazz, classical, pop, etc.) to audio recordings. Introduced formally by Tzanetakis and Cook (2002), it is one of the earliest and most studied music information retrieval problems. It remains critical for music discovery, recommendation systems, digital library organization, and music streaming services. Modern systems achieve high accuracy on standard datasets using deep learning.
Källpost
Citat kopierade ordagrant från metodens källpost. Ingen verifiering på källnivå härleds från dem.
- Tzanetakis, G., & Cook, P. (2002). Musical genre classification of audio signals. IEEE Transactions on Speech and Audio Processing, 10(5), 293-302. · DOI 10.1109/tsa.2002.800560
- Sturm, B. L. (2014). The state of the art ten years after A comparison of document content analysis approaches for genre classification of musical audio signals. Journal of the American Society for Information Science and Technology, 65(9), 1757-1766. · URL
- Costa, Y. M., Oliveira, L. S., & Silla Jr, C. N. (2014). An evaluation of convolutional neural networks for music classification using mel-frequency cepstral coefficients. In Proceedings of the International Joint Conference on Neural Networks. · URL
Kuraterade påståenden
Påståenden lagrade i bevisloggen, var och en med sin egen bedömning.
Denna vy hittar inte på en påståendebedömning när loggen saknar en.
Relaterade metoder
Genererade från metodgrafen och visade som maskinföreslagna relationer – inga bevispåståenden härleds.