0 0

Proje Grubu: EEEAG Sayfa Sayısı: 48 Proje No: 110E049 Proje Bitiş Tarihi: 01.04.2013 Metin Dili: Türkçe İndeks Tarihi: 29-07-2022

Sayısal seslerden adli kanıt toplama

Öz:
-
Anahtar Kelime:

Erişim Türü: Erişime Açık
  • L. Alvarez, C. Llerena, ve E. Alexandre, “Application of neural networks to speech/music/noise classification in digital hearing aids,” in ISCGAV-11. WSEAS, 2011, pp. 97–102.
  • M. Barthet, S. Hargreaves, ve M. Sandler, “Speech/music discrimination in audio podcast using structural segmentation and timbre recognition,” in Exploring Music Contents. Springer, 2011, pp. 138–162.
  • H. Beigi, “Audio source classification using speaker recognition techniques,” World Wide Web, 2011.
  • (Chang, 2011) C.-C. Chang ve C.-J. Lin, LIBSVM: A library for support vector machines, http://www.csie.ntu.edu.tw/~cjlin/libsvm/
  • D. Chow ve W. H. Abdulla, “Speaker identification based on log area ratio and gaussian mixture models in narrow-band speech,” in PRICAI-04. Springer, 2004, pp. 901–908.
  • E. Alexandre-Cortizo, M. Rosa-Zurera, ve F. Lopez-Ferreras, “Application of fisher linear discriminant analysis to speech/music classification,” in EUROCON 2005., vol. 2. IEEE, 2005, pp. 1666–1669.
  • R. Y. Da Luo, Weiqi Luo ve J. Huang, “Compression history identification for digital audio signal,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ISASSP), 2012, pp. 1733–1736.
  • D. L. Donoho ve I. M. Johnstone, “Ideal denoising in an orthonormal basis chosen from a library of bases,” Comptes Rendus Acad. Sci., Ser. I, vol. 319, 1994.
  • J. Munoz-Exposito, S. Garcıa-Galan, N. Ruiz-Reyes, ve P. Vera-Candeas, “Adaptive network-based fuzzy inference system vs. other classification algorithms for warped lpc-based speech/music discrimination,” Eng Appl Artif Intel, vol. 20, no. 6, pp. 783–793, 2007.
  • FreeSound, “Free sound effects.” [Online]. Available: www.freesoundeffects.com A. Gray Jr ve J. Markel, “Distance measures for speech processing,” ITASS, vol. 24, no. 5, pp. 380–391, 1976.
  • A. Ghosal, B. C. Dhara, ve S. K. Saha, “Speech/music classification using empirical mode decomposition,” in EAIT-11. IEEE, 2011, pp. 49–52.
  • R. Gonzalez, “Radon-based audio classification features,” in ICME-12. IEEE, 2012, pp. 556–561.
  • M. A. Haque ve J.-M. Kim, “An analysis of content-based classification of audio signals using a fuzzy c-means algorithm,” Multimed Tools Appl, pp. 1–16, 2012.
  • S. Hiçsönmez ve H. T. Sencar, İ. Avcıbaş, “Audio Codec Identification from Coded and Transcoded Audios,” Digital Signal Processing. (Basım aşamasında) DOI information: 10.1016/j.dsp.2013.04.005
  • S. Hiçsönmez, E. Uzun, H. T. Sencar, “Methods for Identifying Traces of Compression in Audio,” IEEE International Conference on Communications, Signal Processing, and their Applications (ICCSPA), Mart, 2013
  • S. Hiçsönmez, E. Uzun, H. T. Sencar, “Ses Üzerindeki Kodlama İzlerinin Tespiti İcin Yontemler,” 21. IEEE Signal İşleme, İletişim and Uygulamaları Kurultayı (SIU), Nisan, 2013
  • S. Hiçsönmez ve H. T. Sencar, İ. Avcıbaş, “Ses Kodlayıcılarının Kodlama Özelliklerine göre Sınıflandırılması,” 20. IEEE Signal İşleme, İletişim and Uygulamaları Kurultayı (SIU), Nisan, 2012
  • S. Hiçsönmez ve H. T. Sencar, İ. Avcıbaş “Audio Codec Identification Through Payload Sampling,” IEEE Workshop on Information Forensics and Security (WIFS), Aralık, 2011
  • Y. Hu ve P. C. Loizou, “Evaluation of objective quality measures for speech enhancement,” TASLP, vol. 16, no. 1, pp. 229–238, 2008.
  • M. Huijbregts ve F. De Jong, “Robust speech/non-speech classification in heterogeneous multimedia content,” Speech Communication, vol. 53, no. 2, pp. 143– 153, 2011.
  • IDEA, “The international dialects of English archive.” http://web.ku.edu/idea/index.htm F. Itakura ve S. Saito, “Analysis synthesis telephony based on the maximum likelihood method,” in ICA-68., vol. 17. pp. C17–C20, 1968.
  • D. Klatt, “Prediction of perceived phonetic distance from critical-band spectra: A first step,” in ICASSP-82., vol. 7. IEEE, 1982, pp. 1278–1281.
  • Y. Lavner ve D. Ruinskiy, “A decision-tree-based algorithm for speech/music classification and segmentation,” EURASIP JASMP, vol. 2009, p. 2, 2009.
  • (Nist, 2001) NIST, A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptogrpahic Applications, NIST Special publication 802-22, 2001 http://csrc.nist.gov/groups/ST/toolkit/rng/documents/SP800-22b.pdf
  • H. Ozer, I. Avcibas, B. Sankur, and N. D. Memon, “Steganalysis of audio based on audio quality metrics,” in Electronic Imaging 2003. SPIE, 2003, pp. 55–66.
  • A. Pikrakis, T. Giannakopoulos, ve S. Theodoridis, “A speech/music discriminator of radio recordings based on dynamic programming and bayesian networks,” Trans. Multimedia, vol. 10, no. 5, pp. 846–857, 2008.
  • M. Qiao, A. H. Sung, ve Q. Liu, “Revealing real quality of double compressed mp3 audio,” in Proceedings of the international conference on Multimedia, ser. MM ’10, 2010, pp. 1011–1014.
  • A. W. Rix, J. G. Beerends, M. P. Hollier ve A. P. Hekstra, “Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs,” in ICASSP-01., vol. 2. IEEE, 2001, pp. 749–752.
  • S. O. Sadjadi, S. Ahadi, ve O. Hazrati, “Unsupervised speech/music classification using one-class support vector machines,” in ICICS-07 IEEE, 2007, pp. 1–5.
  • E. Scheirer ve M. Slaney, “Construction and evaluation of a robust multifeature speech/music discriminator,” in ICASSP-97., vol. 2. IEEE, 1997, pp. 1331–1334.
  • G. Tzanetakis, G. Essl, ve P. Cook, “Audio analysis using the discrete wavelet transform,” in Proc. AMTA, 2001.
  • E. Uzun ve H. T. Sencar, “A Preliminary Examination Technique for Audio Evidence to Distinguish Between Speech and Non-Speech,” Elsevier Speech Communications, 2013 (Değerlendirme aşamasında.)
  • E. Uzun ve H. T. Sencar, “Konuşma ve Müzik İçeren Seslerin Ayrıştırılması,” 20. IEEE Signal İşleme, İletişim and Uygulamaları Kurultayı (SIU), Nisan, 2012
  • R. Yang, Y.-Q. Shi, ve J. Huang, “Defeating fake-quality mp3,” in Proceedings of the 11th ACM workshop on Multimedia and security, 2009, pp. 117–124.
  • J.-H. Song, K.-H. Lee, J.-H. Chang, J. K. Kim, ve N. S. Kim, “Analysis and improvement of speech/music classification for 3gpp2 smv based on gmm,” Signal Process. Lett., vol. 15, pp. 103–106, 2008.
  • S. Voran, “Objective estimation of perceived speech quality. i. development of the measuring normalizing block technique,” Trans. Speech Audio Processing , vol. 7, no. 4, pp. 371–382, 1999.
  • V. Verfaille, U. Zolzer, ve D. Arfib, “Adaptive digital audio effects (a-dafx): A new class of sound transformations,” TASLP, vol. 14, no. 5, pp. 1817–1831, 2006.
  • Voxforge, “Voxforge speech corpus.”: http://voxforge.org/
  • S. Wang, A. Sekey, ve A. Gersho, “An objective measure for predicting subjective quality of speech coders,” J. Select. Areas Commun., vol. 10, no. 5, pp. 819–829, 1992.
  • L. Xie, Z.-H. Fu, W. Feng, ve Y. Luo, “Pitch-density-based features and an svm binary tree approach for multi-class audio classification in broadcast news,” Multimedia systems, vol. 17, no. 2, pp. 101–112, 2011.
  • W. Yang, M. Dixon, ve R. Yantorno, “A modified bark spectral distortion measure which uses noise masking threshold,” in Speech Coding For Telecomm P. IEEE, 1997, pp. 55– 56.
  • W. Yang, “Enhanced modified bark spectral distortion (embsd): An objective speech quality measure based on audible distortion and cognition model,” Ph.D. dissertation, Temple University, 1999.
  • O. H. Kocal, E. Yuruklu, ve I. Avcibas, “Speech steganalysis using chaotic-features”, IEEE Transactions on Information Forensics and Security (2008) 651-661.
  • U. Zölzer, A. Xavier. DAFX: digital audio effects., Vol. 1. New York: Wiley, 2002.
  • V. Zue, S. Seneff, ve J. Glass, “Speech database development at mit: Timit and beyond,” Speech Communication, vol. 9, no. 4, pp. 351–356, 1990.
APA AVCIBAŞ İ, SENCAR H (2013). Sayısal seslerden adli kanıt toplama. , 1 - 48.
Chicago AVCIBAŞ İsmail,SENCAR Hüsrev Taha Sayısal seslerden adli kanıt toplama. (2013): 1 - 48.
MLA AVCIBAŞ İsmail,SENCAR Hüsrev Taha Sayısal seslerden adli kanıt toplama. , 2013, ss.1 - 48.
AMA AVCIBAŞ İ,SENCAR H Sayısal seslerden adli kanıt toplama. . 2013; 1 - 48.
Vancouver AVCIBAŞ İ,SENCAR H Sayısal seslerden adli kanıt toplama. . 2013; 1 - 48.
IEEE AVCIBAŞ İ,SENCAR H "Sayısal seslerden adli kanıt toplama." , ss.1 - 48, 2013.
ISNAD AVCIBAŞ, İsmail - SENCAR, Hüsrev Taha. "Sayısal seslerden adli kanıt toplama". (2013), 1-48.
APA AVCIBAŞ İ, SENCAR H (2013). Sayısal seslerden adli kanıt toplama. , 1 - 48.
Chicago AVCIBAŞ İsmail,SENCAR Hüsrev Taha Sayısal seslerden adli kanıt toplama. (2013): 1 - 48.
MLA AVCIBAŞ İsmail,SENCAR Hüsrev Taha Sayısal seslerden adli kanıt toplama. , 2013, ss.1 - 48.
AMA AVCIBAŞ İ,SENCAR H Sayısal seslerden adli kanıt toplama. . 2013; 1 - 48.
Vancouver AVCIBAŞ İ,SENCAR H Sayısal seslerden adli kanıt toplama. . 2013; 1 - 48.
IEEE AVCIBAŞ İ,SENCAR H "Sayısal seslerden adli kanıt toplama." , ss.1 - 48, 2013.
ISNAD AVCIBAŞ, İsmail - SENCAR, Hüsrev Taha. "Sayısal seslerden adli kanıt toplama". (2013), 1-48.