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Disentangling Voice and Content with Self-Supervision for Speaker Recognition
[article]
2023
arXiv
pre-print
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It is realized with the use of three Gaussian inference layers, each consisting of a learnable transition model that extracts distinct speech components. ...
For speaker recognition, it is difficult to extract an accurate speaker representation from speech because of its mixture of speaker traits and content. ...
Compared to the TSP method
(system #3), the use of Xi (system #4) achieves overall improvements with the 5.02%/4.19% average
reductions in EER/minDCF. ...
arXiv:2310.01128v3
fatcat:opcbs5wqs5h4hlnmhmpkimnfbi
Deep Learning in Diverse Intelligent Sensor Based Systems
2022
Sensors
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
With the rapid development of deep learning technology and its ever-increasing range of successful applications across diverse sensor systems, there is an urgent need to provide a comprehensive investigation ...
This survey serves as a catalyst to accelerate the application and transformation of deep learning in diverse sensor systems. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s23010062
pmid:36616657
pmcid:PMC9823653
fatcat:riifuhqtnrbrrkat26mxummwd4