自然环境背景噪声下基于低维深度特征的手机来源识别

doi:10.12263/DZXB.20200658

电子学报 ›› 2021, Vol. 49 ›› Issue (4): 637-646.DOI: 10.12263/DZXB.20200658

自然环境背景噪声下基于低维深度特征的手机来源识别

苏兆品^1,2,3,4, 吴张倩², 岳峰^2,4, 武钦芳², 张国富^1,2,3,4

1. 大数据知识工程教育部重点实验室(合肥工业大学), 安徽合肥 230601;
2. 合肥工业大学计算机与信息学院, 安徽合肥 230601;
3. 智能互联系统安徽省实验室, 安徽合肥 230009;
4. 工业安全与应急技术安徽省重点实验室(合肥工业大学), 安徽合肥 230601

收稿日期:2020-07-08 修回日期:2020-12-02 出版日期:2021-04-25
- 通讯作者:
- 张国富
- 作者简介:
- 苏兆品 女,1983年8月出生,山东菏泽人.副教授,硕士生导师,CCF会员.2004年和2008年在合肥工业大学分别获得学士和博士学位.主要从事音频信息隐藏、深度学习和进化计算等方面的研究工作.E-mail:szp@hfut.edu.cn;吴张倩 女,1995年1月出生,安徽宿州人.硕士研究生.2017年在安徽中医药大学获得学士学位.从事音频取证和深度学习方面的研究.E-mail:2465231972@qq.com;岳峰男,1981年2月出生,安徽合肥人.副研究员,硕士生导师.2004年、2009年和2015年在合肥工业大学分别获得学士、硕士和博士学位.主要从事软件工程、音频信息隐藏和进化计算等方面的研究工作.E-mail:yuefeng@hfut.edu.cn;武钦芳 女,1996年8月出生,安徽亳州人.硕士研究生.2018年在安徽中医药大学获得学士学位.从事音频取证和软件工程方面的研究.E-mail:1841807170@qq.com
- 基金资助:
- 国家自然科学基金 (No.61573125）; 教育部人文社会科学研究青年基金 (No.19YJC870021，No.18YJC870025）; 安徽省重点研究与开发计划 (No.202004d07020011）; 中央高校基本科研业务费专项资金 (No.PA2020GDKC0015，No.PA2019GDQT0008，No.PA2019GDPK0072）

Source Cell-Phone Identification Under Background Noise Based on Low-Dimensional Deep Features

SU Zhao-pin^1,2,3,4, WU Zhang-qian², YUE Feng^2,4, WU Qin-fang², ZHANG Guo-fu^1,2,3,4

1. Ministry of Education Key Laboratory of Knowledge Engineering with Big Data(Hefei University of Technology), Hefei, Anhui 230601, China;
2. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, Anhui 230601, China;
3. Intelligent Interconnected Systems Laboratory of Anhui Province(Hefei University of Technology), Hefei, Anhui 230009, China;
4. Anhui Provincial Key Laboratory of Industry Safety and Emergency Technology(Hefei University of Technology), Hefei, Anhui 230601, China

Received:2020-07-08 Revised:2020-12-02 Online:2021-04-25 Published:2021-04-25

摘要/Abstract

摘要： 基于语音的手机来源识别是近年来多媒体取证领域中的一个研究热点，但已有研究大都局限于纯净语音或人工背景噪声语音.本文以自然环境背景噪声下的手机语音为研究对象，提出一种基于低维深度特征的手机来源识别方法.首先提取对数域的Mel滤波器组系数作为基本的声学特征，然后输入到时间卷积网络中进行训练，进一步提取能够表征语音设备的深度特征，并利用线性判别分析进行降维，去除高维深度特征中的冗余.最后，将得到的低维深度特征输入到支持向量机中进行分类和识别.在47种不同型号手机录制的37600条自然环境背景噪声语音样本库上的测试结果表明，本文所提方法在自然环境背景噪声下具有更优的识别性能，且对不同品牌、相同品牌不同型号、不同样本长度、不同数据集规模和不同采样率都具有很好的适应性.

关键词: 手机来源识别, 自然环境背景噪声, 低维深度特征, 时间卷积网络, 线性判别分析

Abstract: Identifying cell-phones using recorded speech has become a hot topic in the field of multimedia forensics in recent years.However,most of the existing studies focus on the clean speech or the speech with unnaturally artificial noise.In this paper,the speech with background noise is taken into account and a source cell-phone identification method is presented on the basis of the low-dimensional deep features.First,the logarithmic Mel-filter bank coefficients are extracted as the main acoustic features and input to the temporal convolutional network for training and further extracting the deep features of speech devices.Then,the linear discriminant analysis is used to reduce the size of the high-dimensional deep features and remove the redundancy.Finally,the low-dimensional deep features are used as input to the support vector machine classifier.The experimental results on 47 models of mobile phones and 37600 speech samples with background noise show that the proposed method has better recognition performance and better adaptability to different brands,different models of the same brand,different sampling lengths,different sizes of the dataset,and different sampling rates.

Key words: source cell-phone identification, background noise, low-dimensional deep features, temporal convolutional network, linear discriminant analysis

中图分类号:

TN912.3

苏兆品, 吴张倩, 岳峰, 武钦芳, 张国富. 自然环境背景噪声下基于低维深度特征的手机来源识别[J]. 电子学报, 2021, 49(4): 637-646.

SU Zhao-pin, WU Zhang-qian, YUE Feng, WU Qin-fang, ZHANG Guo-fu. Source Cell-Phone Identification Under Background Noise Based on Low-Dimensional Deep Features[J]. Acta Electronica Sinica, 2021, 49(4): 637-646.

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自然环境背景噪声下基于低维深度特征的手机来源识别

Source Cell-Phone Identification Under Background Noise Based on Low-Dimensional Deep Features

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