Battling voice spoofing: a review, comparative analysis, and generalizability evaluation of state-of-the-art voice spoofing counter measures

A Khan, KM Malik, J Ryan, M Saravanan - Artificial Intelligence Review, 2023 - Springer
With the advent of automated speaker verification (ASV) systems comes an equal and
opposite development: malicious actors may seek to use voice spoofing attacks to fool those …

Audio deepfake detection: A survey

J Yi, C Wang, J Tao, X Zhang, CY Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
Audio deepfake detection is an emerging active topic. A growing number of literatures have
aimed to study deepfake detection algorithms and achieved effective performance, the …

Speaker recognition from raw waveform with sincnet

M Ravanelli, Y Bengio - 2018 IEEE spoken language …, 2018 - ieeexplore.ieee.org
Deep learning is progressively gaining popularity as a viable alternative to i-vectors for
speaker recognition. Promising results have been recently obtained with Convolutional …

A comparative study on recent neural spoofing countermeasures for synthetic speech detection

X Wang, J Yamagishi - arXiv preprint arXiv:2103.11326, 2021 - arxiv.org
A great deal of recent research effort on speech spoofing countermeasures has been
invested into back-end neural networks and training criteria. We contribute to this effort with …

Rawnet: Advanced end-to-end deep neural network using raw waveforms for text-independent speaker verification

J Jung, HS Heo, J Kim, H Shim, HJ Yu - arXiv preprint arXiv:1904.08104, 2019 - arxiv.org
Recently, direct modeling of raw waveforms using deep neural networks has been widely
studied for a number of tasks in audio domains. In speaker verification, however, utilization …

Recent progresses in deep learning based acoustic models

D Yu, J Li - IEEE/CAA Journal of automatica sinica, 2017 - ieeexplore.ieee.org
In this paper, we summarize recent progresses made in deep learning based acoustic
models and the motivation and insights behind the surveyed techniques. We first discuss …

Interpretable convolutional filters with sincnet

M Ravanelli, Y Bengio - arXiv preprint arXiv:1811.09725, 2018 - arxiv.org
Deep learning is currently playing a crucial role toward higher levels of artificial intelligence.
This paradigm allows neural networks to learn complex and abstract representations, that …

Towards directly modeling raw speech signal for speaker verification using CNNs

H Muckenhirn, MM Doss… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Speaker verification systems traditionally extract and model cepstral features or filter bank
energies from the speech signal. In this paper, inspired by the success of neural network …

Advances in anti-spoofing: from the perspective of ASVspoof challenges

MR Kamble, HB Sailor, HA Patil, H Li - APSIPA Transactions on …, 2020 - cambridge.org
In recent years, automatic speaker verification (ASV) is used extensively for voice biometrics.
This leads to an increased interest to secure these voice biometric systems for real-world …

Rawboost: A raw data boosting and augmentation method applied to automatic speaker verification anti-spoofing

H Tak, M Kamble, J Patino, M Todisco… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
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 …