Search Results for author: Ladislav Mošner

Found 9 papers, 4 papers with code

Improving Speaker Verification with Self-Pretrained Transformer Models

no code implementations17 May 2023 Junyi Peng, Oldřich Plchot, Themos Stafylakis, Ladislav Mošner, Lukáš Burget, Jan Černocký

Recently, fine-tuning large pre-trained Transformer models using downstream datasets has received a rising interest.

Speaker Verification

Parameter-efficient transfer learning of pre-trained Transformer models for speaker verification using adapters

no code implementations28 Oct 2022 Junyi Peng, Themos Stafylakis, Rongzhi Gu, Oldřich Plchot, Ladislav Mošner, Lukáš Burget, Jan Černocký

Recently, the pre-trained Transformer models have received a rising interest in the field of speech processing thanks to their great success in various downstream tasks.

Speaker Verification Transfer Learning

Analysis of impact of emotions on target speech extraction and speech separation

1 code implementation15 Aug 2022 Ján Švec, Kateřina Žmolíková, Martin Kocour, Marc Delcroix, Tsubasa Ochiai, Ladislav Mošner, Jan Černocký

One of the factors causing such degradation may be intrinsic speaker variability, such as emotions, occurring commonly in realistic speech.

Speaker Verification Speech Extraction

Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings

3 code implementations28 Mar 2022 Niko Brümmer, Albert Swart, Ladislav Mošner, Anna Silnova, Oldřich Plchot, Themos Stafylakis, Lukáš Burget

In speaker recognition, where speech segments are mapped to embeddings on the unit hypersphere, two scoring backends are commonly used, namely cosine scoring or PLDA.

Speaker Recognition

MultiSV: Dataset for Far-Field Multi-Channel Speaker Verification

1 code implementation11 Nov 2021 Ladislav Mošner, Oldřich Plchot, Lukáš Burget, Jan Černocký

Motivated by unconsolidated data situation and the lack of a standard benchmark in the field, we complement our previous efforts and present a comprehensive corpus designed for training and evaluating text-independent multi-channel speaker verification systems.

Denoising Speaker Verification +1

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