350 rub
Journal Electromagnetic Waves and Electronic Systems №6 for 2017 г.
Article in number:
Time costs reduction of parameters selection for noise reduction algorithms in the speaker identification problem
Type of article: scientific article
UDC: 004.934
Authors:

G.S. Tupitsin – Ph. D. (Eng.), Department of Infocommunication and Radiophysics, 

P.G. Demidov Yaroslavl State University

E-mail: genichyar@genichyar.com

A.I. Topnikov – Ph. D. (Eng.), Associate Professor, Department of Infocommunication and Radiophysics, P.G. Demidov Yaroslavl State University

E-mail: topartgroup@gmail.com

A.L. Priorov – Dr. Sc. (Eng.), Associate Professor, Department of Infocommunication and Radiophysics,  P.G. Demidov Yaroslavl State University

E-mail: andcat@yandex.ru

Abstract:

A quick speaker identification accuracy estimation technique using some objective speech quality measures was proposed. In this paper the combined speech quality measure research to estimate the speaker identification accuracy without speaker identification system was continued. Obtained results indicated the possibility of test speech signals number reducing in order to accelerate speaker identification accuracy estimation while relatively reliability of the results was remained high. It was shown that the proposed method of indirect speaker identification accuracy estimation can be used in the task of parameters selection for noise reduction algorithms for speaker identification system.

Pages: 44-50
References
  1. Matrouf D., W. Ben Kheder, Bousquet P.M., Ajili M., Bonastre J.F. Dealing with additive noise in speaker recognition systems based on i-vector approach // 23rd European Signal Processing Conference (EUSIPCO). 2015. P. 2092−2096.
  2. Zhao X., Wang Y., Wang D. Robust speaker identification in noisy and reverberant conditions // Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2014. V. 22. № 4. P. 3997−4001.
  3. Zheng T.F., L. Li. Robustness-Related Issues in Speaker Recognition. Springer Singapore. 2017.
  4. Ortega-Garcia J., Gonzalez-Rodriguez J. Overview of speech enhancement techniques for automatic speaker recognition // IEEE Proceeding of Fourth International Conference on Spoken Language Processing (ICSLP). 1996. V. 2. P. 929−932.
  5. Tupiczin G.S., Topnikov A.I., Priorov A.L. Metodika oczenki myagkoj maski dlya zadachi predobrabotki zashumlenny’x rechevy’x signalov v sistemax identifikaczii diktora // Uspexi sovremennoj radioe’lektroniki. 2016. № 6. P. 73−80.
  6. Tupiczin G.S. Predobrabotka rechevy’x signalov v sistemax avtomaticheskoj identifikaczii diktora / Dis. … kand. texn. nauk: 05.12.04. Vladimir: Vladimirskij gosudarstvenny’j universitet imeni Aleksandra Grigor’evicha i Nikolaya Grigor’evicha Stoletovy’x. 2015.
  7. Tupiczin G.S., Topnikov A.I., Priorov A.L. Modifikacziya dvuxstupenchatogo algoritma shumopodavleniya dlya uluchsheniya kachestva identifikaczii diktora v usloviyax shumov // Informaczionny’e sistemy’ i texnologii. 2015. № 6. P. 39−47.
  8. Zeinali H., Sameti H., Babaali B. A Fast Speaker Identification Method Using Nearest Neighbor Distance // IEEE International Conference on Signal Processing (ICSP). 2012. P. 6−9.
  9. Tupitsin G., Topnikov A., Priorov A. Two-step noise reduction based on soft mask for robust speaker identification // IEEE 18th Conference of Open Innovations Association and Seminar on Information Security and Protection of Information Technology (FRUCT-ISPIT). 2016. P. 351−356.
  10. Kinnunen T., Karpov E., Franti P. Real-time speaker identification and verification // IEEE Transactions on Audio, Speech and Language Processing. 2006. V. 14. № 1. P. 277−288.
  11. Battula V.K., Gottapu A.N. General Kalman Filter & Speech Enhancement for Speaker Identification // International Journal on Cybernetics & Informatics. 2016. V. 5. № 4. P. 117−126.
  12. Tupiczin G.S., Topnikov A.I. Kombinirovanny’j pokazatel’ kachestva rechevy’x signalov dlya oczenki tochnosti identifikaczii diktorov // Materialy’ 11-j Mezhdunar. nauchno-texnich. konf. «Perspektivny’e texnologii v sredstvax peredachi informaczii». Vladimir. 2015. P. 240−243.
  13. Tupiczin G.S., Topnikov A.I., Priorov A.L. Speaker Recognition Test Framework – programma dlya issledovaniya algoritmov raspoznavaniya diktora // Svidetel’stvo o gosudarstvennoj registraczii programmy’ dlya E’VM № 2015660245 ot 25 sentyabrya 2015 g.
  14. Cummins F., Grimaldi M., Leonard T., Simko J. The CHAINS Speech Corpus: CHAracterizing INdividual Speakers // Proc of SPECOM. 2006. P. 1−6.
  15. Varga A., Steeneken H.J.M. Assessment for automatic speech recognition: II. NOISEX-92: A database and an experiment to study the effect of additive noise on speech recognition systems // Speech Communication. 1993. V. 12. № 3. P. 247−251.
  16. International Telecommunication Union. P. 862: Perceptual evaluation of speech quality (PESQ), an objective method for end-to-end speech quality assessment of narrowband telephone networks and speech codecs / International Telecommunication Union // ITU-T Recommendation. 2001. V. 862. P. 862.
  17. Klatt D. Prediction of perceived phonetic distance from critical-band spectra: A first step // IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 1982. Institute of Electrical and Electronics Engineers. V. 7. P. 1278−1281.
  18. Kondo K. Subjective Quality Measurement of Speech: Signals and Communication Technology. Berlin, Heidelberg: Springer Berlin Heidelberg. 2012.
  19. Tupiczin G.S. Ispol’zovanie rasstoyaniya mezhdu mel-chastotny’mi kepstral’ny’mi koe’fficzientami dlya oczenki tochnosti identifikaczii diktorov // Doklady’ 18-j Mezhdunar. nauchno-texnich. konf. «Problemy’ peredachi i obrabotki informaczii v setyax i sistemax telekommunikaczij». Ryazan’. 2015. P. 98−99.
  20. Boll S. Suppression of acoustic noise in speech using spectral subtraction // IEEE Transactions on Acoustics, Speech, and Signal Processing. 1979. V. 27. № 2. P. 113−120.
  21. Plapous C., Marro C., Mauuary L., Scalart P. A two-step noise reduction technique // IEEE International Conference on Acoustics, Speech and Signal Processing. 2004. V. 1. P. 289−92.
Date of receipt: 22 июня 2017 г.