基于多索引哈希的快速准确歌曲识别方法

Salvatore Serrano, M. Scarpa
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引用次数: 0

摘要

在音频信号处理领域工作的研究人员和公司广泛感兴趣的一项活动是自动识别广播或播放的商业歌曲的实时短节选的能力。为了同时分析多个音频流,很难获得一种能够生成快速算法的鲁棒方法。在本文中,我们比较了使用我们最近提出的针对几种基线方法的算法的特定改进所获得的结果。具体来说,我们介绍了一种基于多索引哈希的方法,该方法可以在非常大的数据集上显著提高指纹搜索的速度。使用MTG-Jamendo数据集(包含超过5万首歌曲)进行的实验结果表明,考虑到性能参数:准确性、精度和查询时间,我们的方法优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast and Accurate Song Recognition: an Approach Based on Multi-Index Hashing
An activity of wide interest for researchers and companies working in the field of audio signal processing is the capability to automatically recognize in real-time short excerpts of broadcast or played commercial songs. It appears quite difficult to obtain a robust approach able to generate a fast algorithm in order to analyze several audio flows at the same time. In this paper, we compare the results obtained using a specific improvement of an algorithm we recently proposed against several baseline approaches. Specifically, we introduced an approach based on Multi-Index Hashing which permits to improve noticeably speed in fingerprints searching also on very large datasets. Experimental results, performed using the MTG-Jamendo dataset, containing more then 50, 000 songs, show our approach outperform the others jointly considering performance parameters: accuracy, precision and query time.
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