计算机应用 ›› 2011, Vol. 31 ›› Issue (05): 1284-1287.DOI: 10.3724/SP.J.1087.2011.01284

• 信息安全 • 上一篇    下一篇

基于言语情境分析的数字语音篡改检测

丁琦1,2,平西建1   

  1. 1.信息工程大学 信息工程学院, 郑州450002
    2.信息工程大学 电子技术学院, 郑州450004
  • 收稿日期:2010-11-01 修回日期:2010-12-29 发布日期:2011-05-01 出版日期:2011-05-01
  • 通讯作者: 丁琦
  • 作者简介:丁琦(1976-),女,河南荥阳人,讲师,博士研究生,主要研究方向:语音处理、信息隐藏、音频取证;平西建(1953-),男,河南新乡人,教授,博士生导师,主要研究方向:数字图像处理、模式识别、信息隐藏。
  • 基金资助:

    国家自然科学基金资助项目(60970142)。

Digital speech tamper detection based on speaking conditions

DING Qi1,2, PING Xi-jian1   

  1. 1. Institute of Information Engineering, Information Engineering University, Zhengzhou Henan 450002, China
    2. Institute of Electronic Technology, Information Engineering University, Zhengzhou Henan 450004, China
  • Received:2010-11-01 Revised:2010-12-29 Online:2011-05-01 Published:2011-05-01

摘要: 针对使用拼接手段的数字语音篡改,提出一种基于言语情境分析的篡改检测方法。该方法从背景噪声分析和说话人状态特征分析两方面入手,把语音信号分为语音部分和静音部分,对包含噪声的各个静音片段各帧提取时域和频域特征,对各语音片段提取韵律特征和音质特征,并分别基于贝叶斯信息准则检测特征的跳变点,通过综合判断得到篡改检测结果。实验结果表明,该方法能够比较准确地检测和定位语音拼接点。

关键词: 数字语音, 篡改检测, 言语情境分析, 背景噪声, 韵律特征, 音质特征

Abstract: An automatic detection method for digital speech tamper by means of stitching was proposed. This method was based on speaking condition analyses, which comprised background noise analysis and speaker fettle analysis. Speech signals were divided into speech and silence segments. For silence segments containing noise, features in time domain and frequency domain were extracted for each frame. For each speech segment, rhythm and timbre features were extracted. Features changing points of the silence segments and speech segments were detected separately based on Bayesian information criterion, and the tamper detection result was obtained by integrative decision. The experimental results show that the proposed method can detect and locate the stitching points accurately.

Key words: digital speech, tamper detection, speaking condition analysis, background noise, prosodic characteristic, speech quality characteristic