Speaker verification using Gaussian mixture model (GMM)

H. Hussain, S. H. Salleh, C. M. Ting, A. K. Ariff, I. Kamarulafizam, R. A. Suraya

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

4 Citations (Scopus)


This paper applies GMM for SV on Malay speech. The speaker models were trained on maximum likelihood estimated. The system was evaluated with 23 client speakers with 56 imposters. Malay clean speech data was used. 20 training of 3.5s utterances are used. The best performance achieved using 256-Gaussian imposter model and 32-Gaussian client model gave 3.01% of EER.

Original languageEnglish
Title of host publication5th Kuala Lumpur International Conference on Biomedical Engineering 2011, BIOMED 2011
Number of pages5
Publication statusPublished - 2011
Externally publishedYes
EventKuala Lumpur International Conference on Biomedical Engineering (BIOMED) 2011 - Kuala Lumpur, Malaysia
Duration: 20 Jun 201123 Jun 2011
Conference number: 5th
https://link.springer.com/book/10.1007/978-3-642-21729-6 (Proceedings)

Publication series

NameIFMBE Proceedings
Volume35 IFMBE
ISSN (Print)1680-0737


ConferenceKuala Lumpur International Conference on Biomedical Engineering (BIOMED) 2011
Abbreviated titleBIOMED 2011
CityKuala Lumpur
Internet address


  • Equal Error Rate
  • Gaussian Mixture Model
  • Speaker Verification

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