Results 51 to 60 of about 2,263,293 (338)
Real-Time, Universal, and Robust Adversarial Attacks Against Speaker Recognition Systems [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020 As the popularity of voice user interface (VUI) exploded in recent years, speaker recognition system has emerged as an important medium of identifying a speaker in many security-required applications and services. In this paper, we propose the first real-
Yi Xie +5 more
semanticscholar +1 more source
Speaker recognition for children's speech [PDF]
Interspeech 2012, 2012 This paper presents results on Speaker Recognition (SR) for children's speech, using the OGI Kids corpus and GMM-UBM and GMM-SVM SR systems. Regions of the spectrum containing important speaker information for children are identified by conducting SR experiments over 21 frequency bands.
Saeid Safavi 0001 +5 more
openaire +2 more sources
Adversarial Attack and Defense Strategies for Deep Speaker Recognition Systems [PDF]
Computer Speech and Language, 2020 Robust speaker recognition, including in the presence of malicious attacks, is becoming increasingly important and essential, especially due to the proliferation of several smart speakers and personal agents that interact with an individual's voice ...
Arindam Jati +5 more
semanticscholar +1 more source
CN-Celeb: A Challenging Chinese Speaker Recognition Dataset [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019 Recently, researchers set an ambitious goal of conducting speaker recognition in unconstrained conditions where the variations on ambient, channel and emotion could be arbitrary.
Yue Fan +9 more
semanticscholar +1 more source
Alexandria Engineering Journal, 2011 This paper reports an approach that depends on Continuous Hidden Markov Models (CHMMs) to identify Arabic speakers automatically from their voices. The Mel-Frequency Cepstral Coefficients (MFCCs) were selected to describe the speech signal.
Hesham Tolba
doaj +1 more source
Universal Adversarial Perturbations Generative Network For Speaker Recognition [PDF]
IEEE International Conference on Multimedia and Expo, 2020 Attacking deep learning based biometric systems has drawn more and more attention with the wide deployment of fingerprint/face/speaker recognition systems, given the fact that the neural networks are vulnerable to the adversarial examples, which have ...
Jiguo Li +7 more
semanticscholar +1 more source
Speaker similarity evaluation of foreign-accented speech synthesis using HMM-based speaker adaptation [PDF]
, 2011 This paper describes a speaker discrimination experiment in which native English listeners were presented with natural and synthetic speech stimuli in English and were asked to judge whether they thought the sentences were spoken by the same person or ...
Karhila, Reima +5 more
core +1 more source
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems [PDF]
IEEE Symposium on Security and Privacy, 2019 Speaker recognition (SR) is widely used in our daily life as a biometric authentication or identification mechanism. The popularity of SR brings in serious security concerns, as demonstrated by recent adversarial attacks.
Guangke Chen +6 more
semanticscholar +1 more source
Deep Learning and Fourier Transform for Speaker Recognition(DLFSR) [PDF]
Fayoum University Journal of EngineeringAutomatic Speaker recognition (ASR) and verification have gained increased visibility and significance in society as speech technology. Speaker recognition has undergone a revolution due to deep learning techniques, specifically deep neural networks ...
Taqwa Sayed, Amr Gody, Sayed Muhammad
doaj +1 more source
Computer Speech and Language, 2020 We present a thorough analysis of the systems developed by the JHU-MIT consortium in the context of NIST speaker recognition evaluation 2018. In the previous NIST evaluation, in 2016, i-vectors were the speaker recognition state-of-the-art.
J. Villalba +11 more
semanticscholar +1 more source