activity
20172021
most citedDeep Speaker Embeddings for Far-Field Speaker Recognition on Short Utterances

5 citations · 7 across the 3 of their papers we have counts for

collaborators

10 papers

cs.SD2021

STC speaker recognition systems for the NIST SRE 2021

Anastasia Avdeeva, Aleksei Gusev, Igor Korsunov +9

This paper presents a description of STC Ltd. systems submitted to the NIST 2021 Speaker Recognition Evaluation for both fixed and open training conditions. These systems consists…

cs.CV2021

Post-training deep neural network pruning via layer-wise calibration

Ivan Lazarevich, Alexander Kozlov, Nikita Malinin

We present a post-training weight pruning method for deep neural networks that achieves accuracy levels tolerable for the production setting and that is sufficiently fast to be run…

cs.SD20205 cited

Deep Speaker Embeddings for Far-Field Speaker Recognition on Short Utterances

Aleksei Gusev, Vladimir Volokhov, Tseren Andzhukaev +11

Speaker recognition systems based on deep speaker embeddings have achieved significant performance in controlled conditions according to the results obtained for early NIST SRE (Sp…

cs.CV2020

Neural Network Compression Framework for fast model inference

Alexander Kozlov, Ivan Lazarevich, Vasily Shamporov +2

In this work we present a new framework for neural networks compression with fine-tuning, which we called Neural Network Compression Framework (NNCF). It leverages recent advances…

cs.CV2019

Lightweight Network Architecture for Real-Time Action Recognition

Alexander Kozlov, Vadim Andronov, Yana Gritsenko

In this work we present a new efficient approach to Human Action Recognition called Video Transformer Network (VTN). It leverages the latest advances in Computer Vision and Natural…

cs.SD2019

STC Speaker Recognition Systems for the VOiCES From a Distance Challenge

Sergey Novoselov, Aleksei Gusev, Artem Ivanov +5

This paper presents the Speech Technology Center (STC) speaker recognition (SR) systems submitted to the VOiCES From a Distance challenge 2019. The challenge's SR task is focused o…