2 citations · 3 across the 3 of their papers we have counts for
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cs.SD2022
How to Leverage DNN-based speech enhancement for multi-channel speaker verification?
Sandipana Dowerah, Romain Serizel, Denis Jouvet +2
Speaker verification (SV) suffers from unsatisfactory performance in far-field scenarios due to environmental noise andthe adverse impact of room reverberation. This work presents…
cs.SD2020★ 2 cited
Data augmentation versus noise compensation for x- vector speaker recognition systems in noisy environments
Mohammad Mohammadamini, Driss Matrouf
The explosion of available speech data and new speaker modeling methods based on deep neural networks (DNN) have given the ability to develop more robust speaker recognition system…
cs.SD2016
Sub-vector Extraction and Cascade Post-Processing for Speaker Verification Using MLLR Super-vectors
A. K. Sarkar, C. Barras, V. B. Le +1
In this paper, we propose a speaker-verification system based on maximum likelihood linear regression (MLLR) super-vectors, for which speakers are characterized by m-vectors. These…