方法证据记录
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Music Genre Classification Algorithm
分类方法记录 · ml-model / music-information-retrieval
- 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
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