Speaker identification using fuzzy i-vector tree

In this paper, we propose a new method for concurrent accuracy and computational efficiency optimization using a fuzzy clusters tree for i-vector speaker identification. The design assumptions and an algorithm for a new type of fuzzy i-vector tree construction were introduced. The obtained solution...

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Bibliographic Details
Published in:Journal of intelligent & fuzzy systems 2019-01, Vol.37 (4), p.4937-4949
Main Authors: Gałka, Jakub, Jaciów, Paweł
Format: Article
Language:English
Subjects:
Algorithms
Audio equipment
Error reduction
Machine learning
Optimization
Speech recognition
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Summary:In this paper, we propose a new method for concurrent accuracy and computational efficiency optimization using a fuzzy clusters tree for i-vector speaker identification. The design assumptions and an algorithm for a new type of fuzzy i-vector tree construction were introduced. The obtained solution was evaluated using the NIST 2014 i-Vector Speaker Recognition Machine Learning Challenge dataset. A 15% relative equal error rate reduction for a 74% reduction in computation time was achieved when compared to the baseline with only a 5.5% relative identification rate loss for discussed tree configurations.
ISSN:1064-1246
1875-8967
DOI:10.3233/JIFS-181359