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pro vyhledávání: '"Makarov, Rostislav"'
Autor:
Yakovlev, Ivan, Makarov, Rostislav, Balykin, Andrei, Malov, Pavel, Okhotnikov, Anton, Torgashov, Nikita
In this paper, we present Reshape Dimensions Network (ReDimNet), a novel neural network architecture for extracting utterance-level speaker representations. Our approach leverages dimensionality reshaping of 2D feature maps to 1D signal representatio
Externí odkaz:
http://arxiv.org/abs/2407.18223
Autor:
Yakovlev, Ivan, Melnikov, Mikhail, Bukhal, Nikita, Makarov, Rostislav, Alenin, Alexander, Torgashov, Nikita, Okhotnikov, Anton
Publikováno v:
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 6612-6616
The latest research in the field of voice anti-spoofing (VAS) shows that deep neural networks (DNN) outperform classic approaches like GMM in the task of presentation attack detection. However, DNNs require a lot of data to converge, and still lack g
Externí odkaz:
http://arxiv.org/abs/2309.17298
Autor:
Torgashov, Nikita, Makarov, Rostislav, Yakovlev, Ivan, Malov, Pavel, Balykin, Andrei, Okhotnikov, Anton
This report describes ID R&D team submissions for Track 2 (open) to the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). Our solution is based on the fusion of deep ResNets and self-supervised learning (SSL) based models trained on a mixture
Externí odkaz:
http://arxiv.org/abs/2308.08294