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Speaker Detection Using Phoneme Specific Hidden Markov Models

  • Edvin Pakoci
  • Nikša Jakovljević
  • Branislav Popović
  • Dragiša Mišković
  • Darko Pekar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8773)

Abstract

The paper presents a speaker detection system based on phoneme specific hidden Markov model in combination with Gaussian mixture model. Our motivation stems from the fact that the phoneme specific HMM system can model temporal variations and provides possibility to ponder the scores of specific phonemes as well as efficient pruning. The performance of the system has been evaluated on speech database which contains utterances in Serbian from 250 speakers (10 of them being the target speakers). The proposed model is compared to a system based on Gaussian mixture model - universal background model, and showed a significant improvement in detection performance.

Keywords

Speaker detection Hidden Markov models Gaussian mixture models 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Edvin Pakoci
    • 1
  • Nikša Jakovljević
    • 1
  • Branislav Popović
    • 1
  • Dragiša Mišković
    • 1
  • Darko Pekar
    • 1
  1. 1.Faculty of Technical SciencesUniversity of Novi SadSerbia

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