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conference paper
DNN based speaker embedding using content information for text-dependent speaker verification
2018
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
In this paper, we are interested in exploring Deep Neural Network (DNN) based speaker embedding for Random-digit task using content information. To this end, a technique is applied to automatically select common phonetic units between the enrollment and test data to produce speaker verification scores. Furthermore, a novel approach is proposed to incorporate content information in the DNN directly. It is hypothesized that features extracted using this DNN will be helpful for the task. Experiments on the RSR dataset show that the proposed method outperforms the baseline i-vector system by 43% relative equal error rate.
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Type
conference paper
Authors
Dey, Subhadeep
•
Koshinaka, Takafumi
•
Motlicek, Petr
•
Madikeri, Srikanth
Publication date
2018
Published in
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Start page
5344
End page
5348
URL
EPFL units
Available on Infoscience
July 26, 2018