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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: Research of Speech Signal Acoustic Models for Speaker Recognition
Unique Id: IJSDR1806017
Published In: Volume 3 Issue 6, June-2018
Abstract: The research of speech signal acoustic models for speaker recognition been described in this paper. The aim of this research – to investigate acoustic speech signal models suitable for speaker recognition. In the analytical practical part, voice records were investigated, MFCC features were extracted, acoustic speech signal models were trained and tested. Furthermore, investigation results have shown that components in records distributed differently. The six most common acoustic models components were chosen. The most common voice and background components are different. Statistical analysis has shown that log-likelihoods are not statistically significant different for different languages records when same type and same languages acoustic models were applied. Moreover, log-likelihoods are not statistically significant different for different languages records when English acoustic models were used. Finally, log-likelihoods differ mostly in Spanish and English language records. Increasing the number of English and Spanish records log-likelihoods are statistically significant different when English acoustic models are used.
Keywords: MFCC features, GMM, speaker recognition, acoustic model.
Cite Article: "Research of Speech Signal Acoustic Models for Speaker Recognition ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 6, page no.78 - 81, June-2018, Available :http://www.ijsdr.org/papers/IJSDR1806017.pdf
Downloads: 000201506
Publication Details: Published Paper ID: IJSDR1806017
Registration ID:180375
Published In: Volume 3 Issue 6, June-2018
DOI (Digital Object Identifier):
Page No: 78 - 81
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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