Unsupervised intra-speaker variability compensation based on Gestalt and model adaptation in speaker verification with telephone speech

2008 ◽  
Vol 50 (11-12) ◽  
pp. 953-964 ◽  
Author(s):  
Nestor Becerra Yoma ◽  
Claudio Garretón ◽  
Carlos Molina ◽  
Fernando Huenupán
Keyword(s):  
Speaker Verification ◽  
Model Adaptation ◽  
Speaker Variability ◽  
Variability Compensation ◽  
Telephone Speech

Intra-speaker variability compensation in speaker verification with limited enrolling data

2006 ◽  
Author(s):  
Claudio Garreton ◽  
Nestor Becerra Yoma ◽  
Carlos Molina ◽  
Fernando Huenupan
Keyword(s):  
Speaker Verification ◽  
Speaker Variability ◽  
Variability Compensation

Confidence measure based unsupervised target model adaptation for speaker verification

2007 ◽  
Author(s):  
A. Preti ◽  
Jean-François Bonastre ◽  
Driss Matrouf ◽  
F. Capman ◽  
B. Ravera
Keyword(s):  
Speaker Verification ◽  
Model Adaptation ◽  
Confidence Measure ◽  
Target Model

Mean-Delta Features for Telephone Speech Endpoint Detection

2014 ◽  
Vol 12 (3-4) ◽  
pp. 36-44
Author(s):  
A. Ouzounov
Keyword(s):  
Dynamic Time Warping ◽  
Group Delay ◽  
Speaker Verification ◽  
Verification Task ◽  
Endpoint Detection ◽  
Time Warping ◽  
The Mean ◽  
Telephone Speech ◽  
Dynamic Time ◽  
Speech Endpoint Detection

Abstract In this paper, a brief summary of the author’s research in the field of the contour-based telephone speech Endpoint Detection (ED) is presented. This research includes: development of new robust features for ED – the Mean-Delta feature and the Group Delay Mean-Delta feature and estimation of the effect of the analyzed ED features and two additional features in the Dynamic Time Warping fixed-text speaker verification task with short noisy telephone phrases in Bulgarian language.

scholarly journals Telephone Speech Endpoint Detection using Mean-Delta Feature

2014 ◽  
Vol 14 (2) ◽  
pp. 127-139 ◽  
Author(s):  
Atanas Ouzounov
Keyword(s):  
Dynamic Time Warping ◽  
Speaker Verification ◽  
Verification Task ◽  
Endpoint Detection ◽  
Time Warping ◽  
Energy Entropy ◽  
Telephone Speech ◽  
Dynamic Time ◽  
Teager Energy ◽  
Speech Endpoint Detection

Abstract In the study the efficiency of three features for trajectory-based endpoint detection is experimentally evaluated in the fixed-text Dynamic Time Warping (DTW) - a based speaker verification task with short phrases of telephone speech. The employed features are Modified Teager Energy (MTE), Energy-Entropy (EE) feature and Mean-Delta (MD) feature. The utterance boundaries in the endpoint detector are provided by means of state automaton and a set of thresholds based only on trajectory characteristics. The training and testing have been done with noisy telephone speech (short phrases in Bulgarian language with length of about 2 s) selected from BG-SRDat corpus. The results of the experiments have shown that the MD feature demonstrates the best performance in the endpoint detection tests in terms of the verification rate.

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