文献类型：期刊文献

中文题名：基于Gammachirp耳蜗能量谱特征提取的音频指纹算法

英文题名：Audio Fingerprinting Algorithm Based on Feature Extraction of Gammachirp-Cochleagram

作者：孟建华[1];陈宁[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2015

卷号：41

期号：5

起止页码：666

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

基金：国家自然科学基金(61271349)

语种：中文

中文关键词：音频指纹;Gammachirp滤波器组;非负矩阵分解

外文关键词：audio fingerprinting; Gammachirp filter bank; non-negative matrix factorization

摘要：提出了基于Gammachirp耳蜗能量谱的音频时频域特征表示方法,并在此基础上进一步构造了一种音频指纹算法。首先利用非负矩阵分解(Non-negative Matrix Factorization,NMF)提取Gammachirp耳蜗能量谱的局部特征,然后对该局部特征进行差分和量化,以提高算法的鲁棒性,并降低检索的计算复杂度。实验结果表明:在经受音频编辑软件多种攻击和实际环境中录音检索时,本文算法都具有很好的鲁棒性和识别率。
By means of Gammachirp-cochleagram, this paper presents a novel time-frequency representation algorithm for audio features. The local feature of the Gammachirp-cochleagram is firstly extracted by non-negative matrix factorization （NMF）. And then, both the difference and the quantization are applied on the extracted features to further enhance its robustness and reduce its computational complexity. Experimental results illustrate that the proposed algorithm achieves superior performance in robustness and identification rate under the attack of audio editing software and the searching of record.