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基于言语情境分析的数字语音篡改检测 被引量:2

Digital speech tamper detection based on speaking conditions
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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。 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.
作者 丁琦 平西建
出处 《计算机应用》 CSCD 北大核心 2011年第5期1284-1287,共4页 journal of Computer Applications
基金 国家自然科学基金资助项目(60970142)
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 digital speech tamper detection speaking condition analysis background noise prosodic characteristic speech quality characteristic
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参考文献12

  • 1丁琦,平西建.基于子带谱平滑度的音频篡改检测[J].应用科学学报,2010,28(2):142-146. 被引量:6
  • 2施少培,杨旭,陈晓红,卞新伟,奚建华,孙维龙,徐彻,钱煌贵.手机通话语音的实验研究[J].中国司法鉴定,2008(5):39-44. 被引量:2
  • 3姚秋明,柴佩琪,宣国荣,杨志强,施云庆.基于期望最大化算法的音频取证中的篡改检测[J].计算机应用,2006,26(11):2598-2601. 被引量:13
  • 4贾磊,穆向禺,徐波.广播语音的音频分割[J].中文信息学报,2002,16(1):37-42. 被引量:11
  • 5金学成.基于语音信号的情感识别研究[D]中国科学技术大学,中国科学技术大学2007.
  • 6GRIGORAS C.Digital audio recording analysis,the Electric Net-work Frequency (ENF)criterion. International Journal ofSpeech,Language and the Law . 2005
  • 7NICOLALDE D P,APOLINARIO J A.Evaluating digital audio au-thenticity with spectral distances and ENF phase change. IEEE International Conference on Acoustics,Speech and Signal Pro-cessing . 2009
  • 8KRAETZER C,OERMANN A,DITTMANN J,et al.Digital audioforensics:A first practical evaluation on microphone and environ-ment classification. Proceedings of the ACM Multimedia andSecurity Workshop . 2007
  • 9GARCIA-ROMERO D,ESPY-WILSON C Y.Automatic acquisitiondevice identification from speech recordings. IEEE Interna-tional Conference on Acoustics,Speech and Signal Processing . 2010
  • 10GUILLEMIN B J,WATSON C I.Impact of the GSM AMR speechcodec on formant information important to forensic speaker identifica-tion. Proceedings of the 11th Australian International Confer-ence on Speech Science&Technology . 2006

二级参考文献23

  • 1姚秋明,柴佩琪,宣国荣,杨志强,施云庆.基于期望最大化算法的音频取证中的篡改检测[J].计算机应用,2006,26(11):2598-2601. 被引量:13
  • 2KRAETZER C, OERMANN A, DITTMANN J, LANG A. Digital audio forensics: a first practical evaluation on microphone and environment classification[C]//Proceeding of ACM MMSEC'07, Dallas, Texas, 2007: 63-74.
  • 3GRIGORAS C. Digital audio recording analysis the electric network frequency criterion[J]. International Journal of Speech, Language and the Law, 2005, 12: 63-76.
  • 4NICOLALDE D P, APOLINARIO J A. Evaluating digital audio authenticity with spectral distances and ENF phase change [C]//IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, Taiwan, 2009: 1417-1420.
  • 5OERMANN A, LANG A, DITTMANN J. Verifyer-tupel for audio-forensic to determine speaker environment [C]//Proceedings of the ACM Multimedia and Security Workshop 2005, New York, USA, 2005: 57-62.
  • 6奥本海姆AV,谢弗RW,巴克JR.离散时间信号处理[M].第2版.西安:西安交通人学出版社,2001:135-145.
  • 7MONSON H HAYES. Schaum's outline of digital signal processing[M]. New York: McGraw-Hill, 1999: 110-114.
  • 8[1]R. Bakis et al., Transcription of broadcast news shows with the IBM large vocabulary speech recognition system, proceedings of the Speech Recognition Workshop, 1997,67-72,1997
  • 9[2]F. Kubala et al. The 1996 BBN Byblos Hub-4 transcription system, Proceedings of the Speech Recognition Workshop, 1997,90-93
  • 10[3]M. Siegler, U. Jain, B. Ray and R. Stem, Automation segment, classification and clustering of broadcast news audio, Proceedings of the Speech Recognition Workshop, 1997,97-99

共引文献25

同被引文献17

  • 1黄品高.随机共振数值仿真的快速算法[J].系统仿真技术,2006,2(3):155-158. 被引量:2
  • 2莫莉莉.论真实录音材料的语境特征[J].外语与外语教学,2001(5):40-41. 被引量:10
  • 3蔡锦恩,赵文礼.随机共振原理在微弱信号检测中的应用[J].杭州电子科技大学学报(自然科学版),2005,25(1):26-29. 被引量:2
  • 4B Roberto, S Alfonso, V Angelo. The mechanism of stochastic res- onance[J]. J. Phys. A: Math. Gen. 14, 1981:L453-IA57.
  • 5WKurt, M Frank. Stochastic resonance and the benefits of noise : from ice ages to crayfish and SQUIDs[J]. Nature. 373, 1995:33 - 36.
  • 6J M G Vilar, J M Rubi. Noise suppression by noise [ J ]. Physical Review Letters, 2001,86 (6) :950 - 953.
  • 7Grigoras C. Digital Audio Recording Analysis: The Electric Network Frequency(ENF) Criterion[J]. Inter- national Journal of Speech, Language and the Law, 2005, 12(1): 63-76.
  • 8NIcolalde D P, Apolinario J A. Evaluating Digital Audio Authenticity with Spectral Distances and ENF Phase Change[C]//Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing. [S.l.]: IEEE Press, 2009: 1417-1420.
  • 9Roberto B, Alfonso S, Angelo V. The Mechanism of Stochastic Resonance[J]. Journal of Physical A: Mathematical and General, 1981, 14(3): 453-457.
  • 10Wiesenfeld K, Moss F. Stochastic Resonance and The Benefits of Noise: From Ice Ages to Crayfish and Squids[J]. Nature, 1995, 373(6509): 33-36.

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