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音乐分段×音乐流派分类×
领域音乐信息检索音乐信息检索
方法族Machine learningMachine learning
起源年份20012002
提出者Masataka GotoGeorge Tzanetakis
类型Audio structural analysisAudio feature-based classification
开创性文献Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval. link ↗Tzanetakis, G., & Cook, P. (2002). Musical genre classification of audio signals. IEEE Transactions on Speech and Audio Processing, 10(5), 293-302. DOI ↗
别名structural segmentation, music structure analysis, section boundary detectiongenre recognition, music categorization, style classification
相关55
摘要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.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.
ScholarGate数据集
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ScholarGate方法对比: Music Segmentation · Music Genre Classification. 于 2026-06-19 检索自 https://scholargate.app/zh/compare