Title
Improving Robustness of Speaker Verification by Fusion of Prompted Text-Dependent and Text-Independent Operation Modalities.
Abstract
In this paper we present a fusion methodology for combining prompted text-dependent and text-independent speaker verification operation modalities. The fusion is performed in score level extracted from GMM-UBM single mode speaker verification engines using several machine learning algorithms for classification. In order to improve the performance we apply clustering of the score-based data before the classification stage. The experimental results indicated that the fusion of the two operation modes improves the speaker verification performance both in terms of sensitivity and specificity by approximately 2 % and 1.5 % respectively.
Year
DOI
Venue
2016
10.1007/978-3-319-43958-7_45
Lecture Notes in Computer Science
Keywords
Field
DocType
Speaker verification,Fusion,Machine learning
Speaker verification,Modalities,Pattern recognition,Computer science,Fusion,Robustness (computer science),Speech recognition,Artificial intelligence,Cluster analysis
Conference
Volume
ISSN
Citations 
9811
0302-9743
2
PageRank 
References 
Authors
0.37
10
3
Name
Order
Citations
PageRank
Iosif Mporas117640.03
Saeid Safavi220.37
Reza Sotudeh3418.69