Performance Evaluation of Acoustic-Spectrographic Voice Identification Method in Native and Non-Native Speech
The paper deals with acoustic-spectrographic voice
identification method in terms of its performance in non-native
language speech. Performance evaluation is conducted by comparing
the result of the analysis of recordings containing native language
speech with recordings that contain foreign language speech. Our
research is based on Tajik and Russian speech of Tajik native
speakers due to the character of the criminal situation with drug
trafficking. We propose a pilot experiment that represents a primary
attempt enter the field.
[1] T. I. Goloshchapova, Yu. A., Elemeshina, “Expert-Linguistic Methods
for Identification of Tajik Native Speakers,” in The 20th International
Science Conference on Informatization and Information Protection of
Law Enforcement, 2011, pp. 402-405.
[2] S. L. Koval, P. I. Zubova, “Speaker identification by his voice and
speech on the basis of complex analysis of phonograms,” Theory and
practice of forensic expertise, № 3 (7), pp. 68-76, Dec. 2007.
[3] U. Bhattacharjee, K. Sarmah, “Speaker Verification Using Acoustic and
Prosodic Features.” Advanced Computing International Journal, vol. 4,
1, pp. 45-51, Jan. 2013.
[4] A. R. Butcher, “Forensic Phonetics: Issues in Speaker Identification
Evidence,” in Inaugural International Conference of the Institute of
Forensic Studies, 2002, pp. 3-5.
[5] K. Simonchik, T. Pekhovsky, A Shulipa, A. Afanasyev, “Supervised
Mixture of PLDA Models for Cross-Channel Speaker Verification,” in
Interspeech-2012, http://speechprousa.
com/files/filefield_stats/1798/1171/0/bf1ea2362f49c270c85a812b7b
8e8311
[6] The NIST year 2010 speaker recognition evaluation plan,
http://www.itl.nist.gov/iad/mig/tests/spk/2010/NIST_SRE10_evalplan.r6
.pdf
[7] S. Aleinik, Yu. Matveev, A. Raev, “Method of Evaluation of Speech
signal clipping level,” Scientific and Technical Journal of Information
Technologies, Mechanics, and Optics, vol. 79, 3, pp. 79-83, May 2012.
[8] Y. Matveev, K. Simonchik, “The Speaker Identification System for the
NIST SRE 2010,” in The 20th International Conference on Computer
Graphics and Vision, GraphiCon, 2010, pp. 315-319.
[9] A. Kozlov, O. Kudashev, Yu. Matveev, T. Pekhovsky, K. Simonchik, A.
Shulipa, “SVID Speaker Recognition System for NIST SRE 2012,” in
Speech and Computer: Lecture Notes in Computer Science, 2013, vol.
8113, pp. 278-285.
[10] C. S. Greenberg, A. F. Martin, L. Brandschain, J. P. Campbell, Ch.
Cieri, G. R. Doddington, J. J. Godfrey, “Human Assisted Speaker
Recognition in NIST SRE10,” in Odyssey, 2010, pp. 180-185.
[1] T. I. Goloshchapova, Yu. A., Elemeshina, “Expert-Linguistic Methods
for Identification of Tajik Native Speakers,” in The 20th International
Science Conference on Informatization and Information Protection of
Law Enforcement, 2011, pp. 402-405.
[2] S. L. Koval, P. I. Zubova, “Speaker identification by his voice and
speech on the basis of complex analysis of phonograms,” Theory and
practice of forensic expertise, № 3 (7), pp. 68-76, Dec. 2007.
[3] U. Bhattacharjee, K. Sarmah, “Speaker Verification Using Acoustic and
Prosodic Features.” Advanced Computing International Journal, vol. 4,
1, pp. 45-51, Jan. 2013.
[4] A. R. Butcher, “Forensic Phonetics: Issues in Speaker Identification
Evidence,” in Inaugural International Conference of the Institute of
Forensic Studies, 2002, pp. 3-5.
[5] K. Simonchik, T. Pekhovsky, A Shulipa, A. Afanasyev, “Supervised
Mixture of PLDA Models for Cross-Channel Speaker Verification,” in
Interspeech-2012, http://speechprousa.
com/files/filefield_stats/1798/1171/0/bf1ea2362f49c270c85a812b7b
8e8311
[6] The NIST year 2010 speaker recognition evaluation plan,
http://www.itl.nist.gov/iad/mig/tests/spk/2010/NIST_SRE10_evalplan.r6
.pdf
[7] S. Aleinik, Yu. Matveev, A. Raev, “Method of Evaluation of Speech
signal clipping level,” Scientific and Technical Journal of Information
Technologies, Mechanics, and Optics, vol. 79, 3, pp. 79-83, May 2012.
[8] Y. Matveev, K. Simonchik, “The Speaker Identification System for the
NIST SRE 2010,” in The 20th International Conference on Computer
Graphics and Vision, GraphiCon, 2010, pp. 315-319.
[9] A. Kozlov, O. Kudashev, Yu. Matveev, T. Pekhovsky, K. Simonchik, A.
Shulipa, “SVID Speaker Recognition System for NIST SRE 2012,” in
Speech and Computer: Lecture Notes in Computer Science, 2013, vol.
8113, pp. 278-285.
[10] C. S. Greenberg, A. F. Martin, L. Brandschain, J. P. Campbell, Ch.
Cieri, G. R. Doddington, J. J. Godfrey, “Human Assisted Speaker
Recognition in NIST SRE10,” in Odyssey, 2010, pp. 180-185.
@article{"International Journal of Information, Control and Computer Sciences:73297", author = "E. Krasnova and E. Bulgakova and V. Shchemelinin", title = "Performance Evaluation of Acoustic-Spectrographic Voice Identification Method in Native and Non-Native Speech", abstract = "The paper deals with acoustic-spectrographic voice
identification method in terms of its performance in non-native
language speech. Performance evaluation is conducted by comparing
the result of the analysis of recordings containing native language
speech with recordings that contain foreign language speech. Our
research is based on Tajik and Russian speech of Tajik native
speakers due to the character of the criminal situation with drug
trafficking. We propose a pilot experiment that represents a primary
attempt enter the field.", keywords = "Speaker identification, acoustic-spectrographic
method, non-native speech.", volume = "8", number = "10", pages = "1965-4", }
