Automation and Remote Control

, Volume 74, Issue 7, pp 1225–1232 | Cite as

Phonetic words decoding software in the problem of Russian speech recognition

  • A. V. Savchenko
Control Systems and Information Technologies


The prototype of the isolated words recognition software based on the phonetic decoding method with the Kullback-Leibler divergence is presented. The architecture and basic algorithms of the software are described. Finally, an example of application to the problem of isolated words recognition is provided.


Remote Control Speech Recognition Speech Signal Automatic Speech Recognition Continuous Speech 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Sorokin, V.N., Fundamental Study of Speech and Applied Problems of Speech Technologies, Rechevye Tekhnol., 2008, no. 1, pp. 18–48.Google Scholar
  2. 2.
    Babin, D.N., Mazurenko, I.L., and Kholodenko, A.B., On Prospects of Designing an Automatic Recognition System for Continuous Russian Speech, Intellektual. Sist., 2004, vol. 8(1–4), 45–70.Google Scholar
  3. 3.
    Ronzhin, A.L. and Li, I.V., Automatic Recognition of Russian Speech, Vestn. Ross. Akad. Nauk, 2007, vol. 77, no. 2, pp. 133–138.Google Scholar
  4. 4.
    Schuster, M., Speech Recognition for Mobile Devices at Google, in Lecture Notes in Computer Science, 2010, vol. 6230, pp. 8–10.CrossRefGoogle Scholar
  5. 5.
    Grant, R. and McGregor, P.E., Speech Recognition System and Method, US Patent 8 175 883 B3, 2012.Google Scholar
  6. 6.
    Huijbregts, M. and Wooters, C., The Blame Game: Performance Analysis of Speaker Diarization System Components, in Proc. Interspeech, 2007, pp. 27–31.Google Scholar
  7. 7.
    Anusuya, M.A. and Katti, S.K., Speech Recognition by Machine: A Review, Int. J. Computer Sci. Inf. Security, 2009, vol. 6, no. 3.Google Scholar
  8. 8.
    Savchenko, A.V., Automatic Speech Transcription Based on Minimum Information Discrimination Principle, Vestn. Komp. Inform. Tekhnol., 2012, no. 8, pp. 14–19.Google Scholar
  9. 9.
    Savchenko, A.V., Savchenko, V.V., and Akat’ev, D.Yu., A Device for Phonetic Analysis and Recognition of Speech, Offits. Byull. Federal. Sluzh. Intel. Sobstv., Patent. Tovarnym Znakam, 2011, registr. number 2011125526/08.Google Scholar
  10. 10.
    Belyavskii, V.M. and Svetozarova, N.D., Syllable Phonetics and Three Phonetics of L.V. Shcherba, in Teoriya yazyka, metody ego issledovaniya i prepodavaniya (The Theory of Language, Methods of Its Analysis and Teaching), Leningrad: Nauka, 1981, pp. 36–40.Google Scholar
  11. 11.
    Sirigos, J., Fakotakis, N., and Kokkinakis, G., A Hybrid Syllable Recognition System Based on Vowel Spotting, Speech Commun., 2002, vol. 38, pp. 427–440.zbMATHCrossRefGoogle Scholar
  12. 12.
    Savchenko, A.V., Words Phonetic Decoding Method in a Problem of Speech Automatic Recognition on the Basis of InformationMismatchMinimum Principle, Izv. Vyssh. Uchebn. Zaved. Ross., Radioelektron., 2009, no. 5, pp. 31–41.Google Scholar
  13. 13.
    Kullback, S., Information Theory and Statistics, New York: Dover, 1997.zbMATHGoogle Scholar
  14. 14.
    Savchenko, V.V., The Development of Phonetic Algorithms of Speech Recognition and Diarization with Automatically Reconfigurable Dictionary, Sist. Upravlen. Inform. Tekhnol., 2012, no. 3(49), pp. 99–104.Google Scholar
  15. 15.
    Savchenko, V.V. and Savchenko, A.V., The Procedure of Working Dictionary Formation in Automatic Speech Recognition Systems by a Topical Text File, Sist. Upravlen. Inform. Tekhnol., 2012, no. 2.2(48), pp. 284–289.Google Scholar
  16. 16.
    Marple, S.L., Digital Spectral Analysis with Applications, Englewood Cliffs: Prentice Hall, 1987. Translated under the title Tsifrovoi spektral’nyi analiz i ego prilozheniya, Moscow: Mir, 1990.Google Scholar
  17. 17.
    Janakiraman, R., Kumar, J.C., and Murthy, H.A., Robust Syllable Segmentation and Its Application to Syllable-centric Continuous Speech Recognition, in Proc. Natl. Conf. Commun., 2010, pp. 1–5.Google Scholar
  18. 18.
    Kipyatkova, I.S. and Karpov, A.A., Development and Assessment of a Transcribing Module for Recognition and Synthesis of Russian Speech, Iskusstv. Intellekt, 2009, no. 3, pp. 178–185.Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2013

Authors and Affiliations

  • A. V. Savchenko
    • 1
  1. 1.National Research University Higher School of EconomicsNizhni NovgorodRussia

Personalised recommendations