COVER SONG IDENTIFICATION WITH 2D FOURIER TRANSFORM SEQUENCES

被引：0

作者：

Seetharaman, Prem ^{[1
]}

Rafii, Zajar ^{[2
]}

机构：

[1] Northwestern Univ, Evanston, IL 60208 USA

[2] Gracenote Inc, Emeryville, CA USA

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2017年

关键词：

Cover song identification; audio finger-printing; Constant Q transform; 2D Fourier transform; adaptive thresholding;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

We approach cover song identification using a novel time-series representation of audio based on the 2DFT. The audio is represented as a sequence of magnitude 2D Fourier Transforms (2DFT). This representation is robust to key changes, timbral changes, and small local tempo deviations. We look at cross-similarity between these time-series, and extract a distance measure that is invariant to music structure changes. Our approach is state-of-the-art on a recent cover song dataset, and expands on previous work using the 2DFT for music representation and work on live song recognition.

引用

页码：616 / 620

页数：5

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