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תחוםאחזור מידע מוזיקליאחזור מידע מוזיקלי
משפחהMachine learningMachine learning
שנת המקור20022001
הוגה השיטהJeroen HaitsmaMasataka Goto
סוגPerceptual audio hashingAudio structural analysis
מקור מכונןHaitsma, J., & Kalker, T. (2002). A highly robust audio fingerprinting system. In Proceedings of the International Symposium on Music Information Retrieval. link ↗Goto, M., & Hasegawa, Y. (2001). Automatic transcription of popular music audio. In Proceedings of the Fourth International Conference on Music Information Retrieval. link ↗
כינוייםrobust hashing, perceptual hashing, music identificationstructural segmentation, music structure analysis, section boundary detection
קשורות55
תקצירAudio fingerprinting is a technique for creating a compact, robust identifier (fingerprint) for audio recordings that uniquely represents the content while being tolerant to modifications such as compression, noise, or time-shifting. Introduced by Haitsma and Kalker (2002), it underlies music identification services like Shazam and is critical for copyright enforcement, music matching, and library deduplication. A fingerprint is not a waveform hash; it captures perceptual content and remains stable across reasonable audio alterations.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.
ScholarGateמערך נתונים
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  3. PUBLISHED

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ScholarGateהשוואת שיטות: Audio Fingerprinting · Music Segmentation. אוחזר בתאריך 2026-06-19 מתוך https://scholargate.app/he/compare