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Wireless Personal Communications

, Volume 104, Issue 3, pp 895–905 | Cite as

Fusion Multistyle Training for Speaker Identification of Disguised Speech

  • Swati PrasadEmail author
  • Ramjee Prasad
Article
  • 43 Downloads

Abstract

Determining the speaker of a given speech utterance from a group of people is referred to as speaker identification. When voice disguising is done by a person, which is commonly seen in crime scenes, a mismatch between the training and the test speech data occurs, referred to as mismatched problem. It markedly decreases the performance of the speaker identification system. To address this mismatched problem, various multistyle training strategies and a fusion method were previously studied by the authors. This paper further investigates the performance of three multiple-model methods at the decision level for this mismatched problem and compare its performance with the previously studied multistyle training strategies. It is found that the fusion of the two multistyle training strategies, outperformed all other single style training and the multiple-model methods investigated on an average across the different test speech data. This fusion multistyle training technique can be easily employed in a security conscious organization, where monitoring of the employees are required.

Keywords

Multistyle training Multiple-model Voice disguise Robust speaker identification Biometric 

Notes

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringBirla Institute of Technology, MesraRanchiIndia
  2. 2.Department of Business Development and TechnologyAarhus UniversityHerningDenmark

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