An Efficient Music Identification System Based on PostgreSQL User-Defined Functions

In this paper, we present a novel approach for music identification task aimed at proving the ability to identify a song by recorded song snippets. By combining Y. Ke’s feature extracting method [1, 2] with PostgreSQL user-defined functions [3, 4, 5]], our system proves as an effective search strate...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Pham, Cam Ngoc, Nguyen, Hai Chau
التنسيق: مقال
اللغة:English
منشور في: H. : ĐHQGHN 2017
الموضوعات:
الوصول للمادة أونلاين:http://repository.vnu.edu.vn/handle/VNU_123/56441
الوسوم: إضافة وسم
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الوصف
الملخص:In this paper, we present a novel approach for music identification task aimed at proving the ability to identify a song by recorded song snippets. By combining Y. Ke’s feature extracting method [1, 2] with PostgreSQL user-defined functions [3, 4, 5]], our system proves as an effective search strategy for the field. We construct training data sets in a noisy environment and compare the search speed and the search accuracy of the system with Y. Ke’s system. Experiment results show that our system is more powerful with the accurate retrieval ability of 98% on a database of 600 songs and the search speed is 3.6 times faster than Y. Ke’s system.