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Speaker verification with TIMIT corpus-some remarks on classical methods

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The aim of this paper is to present some research on speaker verification system based on Gaussian Mixture Model-Universal Background Model (GMM-UBM) approach. All tests were done for the TIMIT corpus. Performance for the standard Mel-Frequency Cepstral Coefficients (MFCC) and dynamic delta features is shown. Influence of feature dimensionality and model complexity on Equal Error Rate (EER) is presented. Additionally, an impact of Voice Activity Detection (VAD) and normalization techniques like Cepstral Mean and Variance Normalization (CMVN) and RelAtive SpecTrA (RASTA) filtering is covered. Each combination of factors was examined. It is shown that careful selection of traditional techniques may lead to very satisfying results when it comes to achieved EER values.

Original languageEnglish
Title of host publicationSPA 2020 - Signal Processing
Subtitle of host publicationAlgorithms, Architectures, Arrangements, and Applications, Conference Proceedings
PublisherIEEE Computer Society
Pages174-179
Number of pages6
ISBN (Electronic)9788362065394
DOIs
Publication statusPublished - 23 Sept 2020
Event24th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2020 - Virtual, Poznan, Poland
Duration: 23 Sept 202025 Sept 2020

Publication series

NameSignal Processing - Algorithms, Architectures, Arrangements, and Applications Conference Proceedings, SPA
Volume2020-September
ISSN (Print)2326-0262
ISSN (Electronic)2326-0319

Conference

Conference24th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2020
Country/TerritoryPoland
CityVirtual, Poznan
Period23/09/2025/09/20

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems
  • Signal Processing

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