Search Results for author: Hemlata Tak

Found 12 papers, 10 papers with code

t-EER: Parameter-Free Tandem Evaluation of Countermeasures and Biometric Comparators

1 code implementation21 Sep 2023 Tomi Kinnunen, Kong Aik Lee, Hemlata Tak, Nicholas Evans, Andreas Nautsch

The proposed approach is a strong candidate metric for the tandem evaluation of PAD systems and biometric comparators.

Towards single integrated spoofing-aware speaker verification embeddings

1 code implementation30 May 2023 Sung Hwan Mun, Hye-jin Shim, Hemlata Tak, Xin Wang, Xuechen Liu, Md Sahidullah, Myeonghun Jeong, Min Hyun Han, Massimiliano Todisco, Kong Aik Lee, Junichi Yamagishi, Nicholas Evans, Tomi Kinnunen, Nam Soo Kim, Jee-weon Jung

Second, competitive performance should be demonstrated compared to the fusion of automatic speaker verification (ASV) and countermeasure (CM) embeddings, which outperformed single embedding solutions by a large margin in the SASV2022 challenge.

Speaker Verification

Can spoofing countermeasure and speaker verification systems be jointly optimised?

1 code implementation13 Mar 2023 Wanying Ge, Hemlata Tak, Massimiliano Todisco, Nicholas Evans

Spoofing countermeasure (CM) and automatic speaker verification (ASV) sub-systems can be used in tandem with a backend classifier as a solution to the spoofing aware speaker verification (SASV) task.

Speaker Verification

On the potential of jointly-optimised solutions to spoofing attack detection and automatic speaker verification

1 code implementation1 Sep 2022 Wanying Ge, Hemlata Tak, Massimiliano Todisco, Nicholas Evans

The spoofing-aware speaker verification (SASV) challenge was designed to promote the study of jointly-optimised solutions to accomplish the traditionally separately-optimised tasks of spoofing detection and speaker verification.

Speaker Verification

SASV 2022: The First Spoofing-Aware Speaker Verification Challenge

no code implementations28 Mar 2022 Jee-weon Jung, Hemlata Tak, Hye-jin Shim, Hee-Soo Heo, Bong-Jin Lee, Soo-Whan Chung, Ha-Jin Yu, Nicholas Evans, Tomi Kinnunen

Pre-trained spoofing detection and speaker verification models are provided as open source and are used in two baseline SASV solutions.

Speaker Verification

RawBoost: A Raw Data Boosting and Augmentation Method applied to Automatic Speaker Verification Anti-Spoofing

1 code implementation8 Nov 2021 Hemlata Tak, Madhu Kamble, Jose Patino, Massimiliano Todisco, Nicholas Evans

This paper introduces RawBoost, a data boosting and augmentation method for the design of more reliable spoofing detection solutions which operate directly upon raw waveform inputs.

Speaker Verification Voice Anti-spoofing

Graph Attention Networks for Anti-Spoofing

no code implementations8 Apr 2021 Hemlata Tak, Jee-weon Jung, Jose Patino, Massimiliano Todisco, Nicholas Evans

This paper reports our use of graph attention networks (GATs) to model these relationships and to improve spoofing detection performance.

Graph Attention Speaker Verification

End-to-end anti-spoofing with RawNet2

1 code implementation2 Nov 2020 Hemlata Tak, Jose Patino, Massimiliano Todisco, Andreas Nautsch, Nicholas Evans, Anthony Larcher

Spoofing countermeasures aim to protect automatic speaker verification systems from attempts to manipulate their reliability with the use of spoofed speech signals.

Speaker Verification

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