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Identifying Lithuanian Native Speakers Using Voice Recognition

  • Laurynas DovydaitisEmail author
  • Vytautas Rudžionis
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 303)

Abstract

In this paper, we analyze speaker identification and present identification test results on Lithuanian native speakers’ database LIEPA. Two approaches for speaker acoustic modeling are examined. We start by extracting MFCC features from audio samples, then we feed this data to create speaker acoustic model with hidden Markov models (1) and with deep neural networks (2). We compare both methods by nalyzing the subset of samples from LIEPA database. This helps to achieve more than 96% identification accuracy on sample dataset.

Keywords

Speaker identification Deep neural networks Hidden Markov models 

References

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Kaunas FacultyVilnius UniversityKaunasLithuania

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