Multiresolution alignment for multiple unsynchronized audio sequences using Sequential Monte Carlo samplers

被引:0
|
作者
Basaran, Dogac [1 ]
Cemgil, Ali Taylan [2 ]
Anarim, Emin [3 ]
机构
[1] Telecom Paristech Univ, Signal & Image Proc Dept, 46 Rue Barrault, Paris, France
[2] Bogazici Univ, Comp Engn Dept, TR-34342 Istanbul, Turkey
[3] Bogazici Univ, Elect & Elect Engn Dept, TR-34342 Istanbul, Turkey
关键词
Multiple audio alignment; Multiresolution alignment; Audio fingerprint; Bayesian inference; Sequential Monte Carlo samplers; Sequential alignment;
D O I
10.1016/j.softx.2017.11.006
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
With proliferation of smart devices such as smart phones, it is common that an event is recorded by multiple individuals creating several audio and video perspectives. Such user generated content is mostly unorganized (not synchronized). In this work, we consider the problem of aligning of multiple unsynchronized audio sequences and propose a multiresolution alignment algorithm using Sequential Monte Carlo samplers in a course to fine structure. The proposed method is evaluated with a real-life dataset from Jiku Mobile Video Datasets and has proven to be competitive with the baseline fingerprinting based alignment methods, with the proper choice of parameters. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:33 / 38
页数:6
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