مقایسهٔ روشها
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| طبقهبندی ژانr موسیقی× | ردیابی ضرب (Beat Tracking)× | |
|---|---|---|
| حوزه | بازیابی اطلاعات موسیقی | بازیابی اطلاعات موسیقی |
| خانواده | Machine learning | Machine learning |
| سال پیدایش≠ | 2002 | 2007 |
| پدیدآور≠ | George Tzanetakis | David P. Ellis |
| نوع≠ | Audio feature-based classification | Audio signal processing algorithm |
| منبع بنیادین≠ | Tzanetakis, G., & Cook, P. (2002). Musical genre classification of audio signals. IEEE Transactions on Speech and Audio Processing, 10(5), 293-302. DOI ↗ | Ellis, D. P. (2007). Beat tracking by dynamic programming. Journal of New Music Research, 36(1), 51-60. DOI ↗ |
| نامهای دیگر | genre recognition, music categorization, style classification | pulse detection, beat detection, metrical analysis |
| مرتبط | 5 | 5 |
| خلاصه≠ | 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. | Beat tracking is an algorithm for automatically identifying the temporal positions of musical beats in audio recordings. It has been widely studied since the early 2000s, particularly for rhythm analysis and music synchronization applications. The problem is central to music information retrieval and essential for music-aware systems. |
| ScholarGateمجموعهداده ↗ |
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