Results 21 to 30 of about 756,236 (193)
The HCCL Speaker Verification System for Far-Field Speaker Verification Challenge
CoRR, 2021 This paper describes the systems submitted by team HCCL to the Far-Field Speaker Verification Challenge. Our previous work in the AIshell Speaker Verification Challenge 2019 shows that the powerful modeling abilities of Neural Network architectures can provide exceptional performance for this kind of task.
Zhuo Li +5 more
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IEEE Access, 2023 Temporal dynamic convolution neural networks (TDY-CNNs) extract speaker embeddings considering the time-varying characteristics of speech and improve text-independent speaker verification performance.
Seong-Hu Kim, Hyeonuk Nam, Yong-Hwa Park
doaj +1 more source
A Tutorial on Text-Independent Speaker Verification
EURASIP Journal on Advances in Signal Processing, 2004 This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system.
Frédéric Bimbot +9 more
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SpeakerNet for Cross-lingual Text-Independent Speaker Verification
Archives of Acoustics, 2020 Biometrics provide an alternative to passwords and pins for authentication. The emergence of machine learning algorithms provides an easy and economical solution to authentication problems.
Hafsa HABIB +4 more
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The Journal of the Acoustical Society of America, 1966 Speaker verification is defined as the process of confirming the purported identity of an informant. An automatic verification system is required to give a YES-NO decision with a corresponding measure of confidence. It would be desirable to begin with a set of ideal measurements that extract only the parameters in the voice relating to speaker identity.
W. D. Chapman, Kung-Pu Li
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Defending against FakeBob Adversarial Attacks in Speaker Verification Systems with Noise-Adding
Algorithms, 2022 Speaker verification systems use human voices as an important biometric to identify legitimate users, thus adding a security layer to voice-controlled Internet-of-things smart homes against illegal access.
Zesheng Chen +4 more
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Disentangled Speaker and Nuisance Attribute Embedding for Robust Speaker Verification
IEEE Access, 2020 Over the recent years, various deep learning-based embedding methods have been proposed and have shown impressive performance in speaker verification. However, as in most of the classical embedding techniques, the deep learning-based methods are known to
Woo Hyun Kang +3 more
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IEEE Access, 2021 In this paper, we propose self-supervised speaker representation learning strategies, which comprise of a bootstrap equilibrium speaker representation learning in the front-end and an uncertainty-aware probabilistic speaker embedding training in the back-
Sung Hwan Mun +4 more
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Speech and Hearingidentifier:oai:t2r2.star.titech.ac.jp ...
MJ CAREY, E PARRIS, SJ BENNETT
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Rep Works in Speaker Verification
CoRR, 2021 submitted to ICASSP ...
Yufeng Ma +5 more
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