Results 21 to 30 of about 719,897 (244)
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
doaj +1 more source
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
doaj +1 more source
Speaker Verification Based on Single Channel Speech Separation
IEEE Access, 2023 In multi-speaker scenarios, speech processing tasks like speaker identification and speech recognition are susceptible to noise and overlapped voices.
Rong Jin, Mijit Ablimit, Askar Hamdulla
doaj +1 more source
Attention-Based Temporal-Frequency Aggregation for Speaker Verification
Sensors, 2022 Convolutional neural networks (CNNs) have significantly promoted the development of speaker verification (SV) systems because of their powerful deep feature learning capability.
Meng Wang +3 more
doaj +1 more source
jakerenzella/speaker-verification: Research Archive V1.0
, 2021 Research Archive of the Deep Speaker implementation used in the Real Talk ...
Jake Renzella +2 more
core +1 more source
Learnable MFCCs for Speaker Verification [PDF]
2021 IEEE International Symposium on Circuits and Systems (ISCAS), 2021 Accepted to ISCAS ...
Xuechen Liu 0001 +2 more
openaire +5 more sources
Speech and Hearingidentifier:oai:t2r2.star.titech.ac.jp ...
MJ CAREY, E PARRIS, SJ BENNETT
+8 more sources
Employing Emotion Cues to Verify Speakers in Emotional Talking Environments
Journal of Intelligent Systems, 2016 Usually, people talk neutrally in environments where there are no abnormal talking conditions such as stress and emotion. Other emotional conditions that might affect people’s talking tone include happiness, anger, and sadness. Such emotions are directly
Shahin Ismail
doaj +1 more source
The Achilles’ heel of spoofing-aware speaker verification: a module-level analysis of adversarial vulnerabilities [PDF]
PeerJ Computer ScienceSpoofing-aware speaker verification (SASV) systems combine automatic speaker verification (ASV) and spoofing countermeasure (CM) modules to defend against spoofing attacks. However, their vulnerability to adversarial attacks remains underexplored.
Yowon Lee +3 more
doaj +2 more sources
Introducing phonetic information to speaker embedding for speaker verification
EURASIP Journal on Audio, Speech, and Music Processing, 2019 Phonetic information is one of the most essential components of a speech signal, playing an important role for many speech processing tasks. However, it is difficult to integrate phonetic information into speaker verification systems since it occurs ...
Yi Liu +3 more
doaj +1 more source