[PDF][PDF] x-Vectors Meet Adversarial Attacks: Benchmarking Adversarial Robustness in Speaker Verification.
Abstract Automatic Speaker Verification (ASV) enables high-security applications like user
authentication or criminal investigation. However, ASV can be subjected to malicious …
authentication or criminal investigation. However, ASV can be subjected to malicious …
[PDF][PDF] Black-Box Attacks on Spoofing Countermeasures Using Transferability of Adversarial Examples.
Spoofing countermeasure systems protect Automatic Speaker Verification (ASV) systems
from spoofing attacks such as replay, synthesis, and conversion. However, research has …
from spoofing attacks such as replay, synthesis, and conversion. However, research has …
Robust speaker recognition with transformers using wav2vec 2.0
S Novoselov, G Lavrentyeva, A Avdeeva… - arxiv preprint arxiv …, 2022 - arxiv.org
Recent advances in unsupervised speech representation learning discover new
approaches and provide new state-of-the-art for diverse types of speech processing tasks …
approaches and provide new state-of-the-art for diverse types of speech processing tasks …
[PDF][PDF] Spine2Net: SpineNet with Res2Net and Time-Squeeze-and-Excitation Blocks for Speaker Recognition.
Modeling speaker embeddings using deep neural networks is currently state-of-the-art in
speaker recognition. Recently, ResNet-based structures have gained a broader interest …
speaker recognition. Recently, ResNet-based structures have gained a broader interest …
[PDF][PDF] STC Speaker Recognition System for the NIST SRE 2021.
Abstract The 2021 Speaker Recognition Evaluation (SRE21) is the next of an open speaker
recognition evaluations conducted by the US National Institute of Standards and Technology …
recognition evaluations conducted by the US National Institute of Standards and Technology …
[PDF][PDF] On the robustness of wav2vec 2.0 based speaker recognition systems
S Novoselov, G Lavrentyeva, A Avdeeva… - Proc …, 2023 - isca-archive.org
Recent advances in unsupervised speech representation learning discover new
approaches and provide new state-of-the-art for diverse types of speech processing tasks …
approaches and provide new state-of-the-art for diverse types of speech processing tasks …
Representation learning to classify and detect adversarial attacks against speaker and speech recognition systems
Adversarial attacks have become a major threat for machine learning applications. There is
a growing interest in studying these attacks in the audio domain, eg, speech and speaker …
a growing interest in studying these attacks in the audio domain, eg, speech and speaker …
[PDF][PDF] Advances in Cross-Lingual and Cross-Source Audio-Visual Speaker Recognition: The JHU-MIT System for NIST SRE21.
We present a condensed description of the joint effort of JHUCLSP/HLTCOE, MIT-LL and
AGH for NIST SRE21. NIST SRE21 consisted of speaker detection over multilingual …
AGH for NIST SRE21. NIST SRE21 consisted of speaker detection over multilingual …
Deep feature cyclegans: Speaker identity preserving non-parallel microphone-telephone domain adaptation for speaker verification
With the increase in the availability of speech from varied domains, it is imperative to use
such out-of-domain data to improve existing speech systems. Domain adaptation is a …
such out-of-domain data to improve existing speech systems. Domain adaptation is a …
Time-domain speech super-resolution with gan based modeling for telephony speaker verification
Automatic Speaker Verification (ASV) technology has become commonplace in virtual
assistants. However, its performance suffers when there is a mismatch between the train and …
assistants. However, its performance suffers when there is a mismatch between the train and …