Speaker verification with long-term ageing data

2012 ◽  
Author(s):  
Finnian Kelly ◽  
Andrzej Drygajlo ◽  
Naomi Harte
Keyword(s):  
Speaker Verification

Improving speaker verification performance against long-term speaker variability

2016 ◽  
Vol 79 ◽  
pp. 14-29 ◽  
Author(s):  
Linlin Wang ◽  
Jun Wang ◽  
Lantian Li ◽  
Thomas Fang Zheng ◽  
Frank K. Soong
Keyword(s):  
Speaker Verification ◽  
Speaker Variability

scholarly journals LTSD and GDMD features for Telephone Speech Endpoint Detection

2017 ◽  
Vol 17 (4) ◽  
pp. 114-133
Author(s):  
Atanas Ouzounov
Keyword(s):  
Dynamic Time Warping ◽  
Group Delay ◽  
Speaker Verification ◽  
Endpoint Detection ◽  
Time Warping ◽  
Adaptive Thresholds ◽  
Telephone Speech ◽  
Dynamic Time ◽  
Speech Endpoint Detection

AbstractThis paper proposes a new contour-based speech endpoint detector which combines the log-Group Delay Mean-Delta (log-GDMD) feature, an adaptive twothreshold scheme and an eight-state automaton. The adaptive thresholds scheme uses two pairs of thresholds - for the starting and for the ending points, respectively. Each pair of thresholds is calculated by using the contour characteristics in the corresponded region of the utterance. The experimental results have shown that the proposed detector demonstrates better performance compared to the Long-Term Spectral Divergence (LTSD) one in terms of endpoint accuracy. Additional fixed-text speaker verification tests with short phrases of telephone speech based on the Dynamic Time Warping (DTW) and left-to-right Hidden Markov Model (HMM) frameworks confirm the improvements of the verification rate due to the better endpoint accuracy.

scholarly journals Effect of long-term ageing on i-vector speaker verification

2014 ◽  
Author(s):  
Finnian Kelly ◽  
Rahim Saeidi ◽  
Naomi Harte ◽  
David A. van Leeuwen
Keyword(s):  
Speaker Verification

scholarly journals Use of Paraconsistent Feature Engineering to support the Long Term Feature choice for Speaker Verification

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Alex Marino Gonçalves De Almeida ◽  
Claudineia Helena Recco ◽  
Rodrigo Capobianco Guido
Keyword(s):  
Speech Synthesis ◽  
Speaker Verification ◽  
Wavelet Packet ◽  
Voice Conversion ◽  
Feature Engineering ◽  
Discrete Wavelet ◽  
Equal Error Rate ◽  
Discrete Wavelet Packet Transform ◽  
Open Research

The state-of-art models for speech synthesis and voice conversion can generate synthetic speech perceptually indistinguishable from human speech, and speaker verification is crucial to prevent breaches. The building feature that best distinguishes genuine speech between spoof attacks is an open research subject. We used the baseline ASVSpoof2017, Transfer Learning (TL) set, and Symlet and Daubechies Discrete Wavelet Packet Transform (DWPT) for this investigation. To qualitatively assess the features, we used Paraconsistent Feature Engineering (PFE). Our experiments pointed out that for the use of more robust classifiers, the best choice would be the AlexNet method, while in terms of classification regarding the Equal Error Rate metric, the best suggestion would be Daubechies filter support 21. Finally, our findings indicate that Symlet filter support 17 as the most promising feature, which is evidence that PFE is a useful tool and contributes to feature selection.

Therapy and prevention for mental health: What if mental diseases are mostly not brain disorders?

2019 ◽  
Vol 42 ◽  
Author(s):  
John P. A. Ioannidis
Keyword(s):  
Mental Health ◽  
Mental Disease ◽  
Brain Disorders ◽  
Social Stressors ◽  
Labor Education ◽  
Mental Diseases ◽  
Long Term Follow Up ◽  
Political Decisions

AbstractNeurobiology-based interventions for mental diseases and searches for useful biomarkers of treatment response have largely failed. Clinical trials should assess interventions related to environmental and social stressors, with long-term follow-up; social rather than biological endpoints; personalized outcomes; and suitable cluster, adaptive, and n-of-1 designs. Labor, education, financial, and other social/political decisions should be evaluated for their impacts on mental disease.

Conceptual short-term memory (CSTM) supports core claims of Christiansen and Chater

2016 ◽  
Vol 39 ◽  
Author(s):  
Mary C. Potter
Keyword(s):  
Working Memory ◽  
Rapid Serial Visual Presentation ◽  
Language Comprehension ◽  
Short Term Memory ◽  
Visual Presentation ◽  
Long Term Memory ◽  
Short Term ◽  
Term Memory ◽  
Use Of Knowledge

AbstractRapid serial visual presentation (RSVP) of words or pictured scenes provides evidence for a large-capacity conceptual short-term memory (CSTM) that momentarily provides rich associated material from long-term memory, permitting rapid chunking (Potter 1993; 2009; 2012). In perception of scenes as well as language comprehension, we make use of knowledge that briefly exceeds the supposed limits of working memory.

Sign in / Sign up

Export Citation Format

Share Document