Language Identification Using Time Delay Neural Network D-Vector on Short Utterances

  • Maxim Tkachenko
  • Alexander Yamshinin
  • Nikolay Lyubimov
  • Mikhail Kotov
  • Marina Nastasenko
Conference paper

DOI: 10.1007/978-3-319-43958-7_53

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9811)
Cite this paper as:
Tkachenko M., Yamshinin A., Lyubimov N., Kotov M., Nastasenko M. (2016) Language Identification Using Time Delay Neural Network D-Vector on Short Utterances. In: Ronzhin A., Potapova R., Németh G. (eds) Speech and Computer. SPECOM 2016. Lecture Notes in Computer Science, vol 9811. Springer, Cham

Abstract

This paper describes d-vector language identification (LID) system on short utterances using time delay neural network (TDNN) acoustic model for the speech recognition task. The acoustic TDNN model is chosen for ASR system of ICQ messenger and it’s applied for the LID task. We compared LID TDNN d-vector results to i-vector baseline. It was found that the TDNN system performance is close at any durations while i-vector shows good results only at long time. Open-set test is conducted. Relative improvement of 5.5 % over the i-vector system is shown.

Keywords

Language identification I-vector D-vector Speech recognition acoustic model Neural networks 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Maxim Tkachenko
    • 1
  • Alexander Yamshinin
    • 1
  • Nikolay Lyubimov
    • 3
  • Mikhail Kotov
    • 2
  • Marina Nastasenko
    • 1
  1. 1.Vector I LLCMoscowRussia
  2. 2.ASM Solutions LLCMoscowRussia
  3. 3.Lomonosov Moscow State UniversityMoscowRussia

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