Advertisement

Speaker Authentication System Based on Voice Biometrics and Speech Recognition

  • Laurynas DovydaitisEmail author
  • Tomas RasymasEmail author
  • Vytautas RudžionisEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 263)

Abstract

In this paper we are analyzing possibility to authenticate speaker by using user voice biometrics and speech recognition. Process of authentication is simple: user says his personal ID number, then system makes prediction of users’ identity and compares it to claimed ID. If these two parameters are equal system makes a positive decision. Using proposed algorithms we managed to achieve 70.45% accuracy for system, with identification module accuracy of 100% and recognition module accuracy of 70.45%.

Keywords

Voice biometrics Speech recognition Hybrid system 

References

  1. 1.
    Rasymas, T., Rudžionis, V.: Lithuanian digits recognition by using hybrid approach by combining Lithuanian google recognizer and some foreign language recognizers. In: Dregvaite, G., Damasevicius, R. (eds.) ICIST 2015. CCIS, vol. 538, pp. 449–459. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-24770-0_38 Google Scholar
  2. 2.
    Rasymas, T., Rudžionis, V.: Evaluation of methods to combine different speech recognizers. In: Proceedings of the Federated Conference on Computer Science and Information Systems, vol. 5, pp. 1043–1047 (2015). doi: 10.15439/2015F62
  3. 3.
    Rudžionis, V., Ratkevičius, K., Rudžionis, A., Raškinis, G., Maskeliunas, R.: Recognition of voice commands using hybrid approach. In: Skersys, T., Butleris, R., Butkiene, R. (eds.) ICIST 2013. CCIS, vol. 403, pp. 249–260. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-41947-8_21 CrossRefGoogle Scholar
  4. 4.
    Kasparaitis, P.: Transcribing of the Lithuanian text using formal rules. Informatica 10(4), 367–376 (1999)Google Scholar
  5. 5.
    Schultz, T., Waibel, A.: Language-independent and language-adaptive acoustic modeling for speech recognition. Speech Commun. 35(1), 31–52 (2001)CrossRefGoogle Scholar
  6. 6.
    Meneido, H., Neto, J.: Combination of acoustic models in continuous speech recognition hybrid systems. In: Proceedings of the International Conference in Spoken Language Processing, vol. 9, pp. 1000–1029 (2000)Google Scholar
  7. 7.
    Dovydaitis, L., Rudžionis, V.: Asmens balso panaudojimas autentikavimui, Informacinės technologijos 2015. 20-oji tarpuniversitetinė magistrantų ir doktorantų konferencija, pp. 147–151 (2015). ISSN 2029-249XGoogle Scholar
  8. 8.
    Kinnunen, T., Li, H.: An overview of text-independent speaker recognition: from features to supervectors. Speech Commun. 52, 12–40 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Kaunas Faculty of HumanitiesVilnius UniversityKaunasLithuania

Personalised recommendations