Voice Anti-spoofing
12 papers with code • 3 benchmarks • 5 datasets
Discriminate genuine speech and spoofing attacks
Benchmarks
These leaderboards are used to track progress in Voice Anti-spoofing
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ASVspoof 2019
PartialSpoof
ReMASC
Most implemented papers
One-class learning towards generalized voice spoofing detection
Human voices can be used to authenticate the identity of the speaker, but the automatic speaker verification (ASV) systems are vulnerable to voice spoofing attacks, such as impersonation, replay, text-to-speech, and voice conversion.
An Empirical Study on Channel Effects for Synthetic Voice Spoofing Countermeasure Systems
yzyouzhang/Empirical-Channel-CM
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Spoofing countermeasure (CM) systems are critical in speaker verification; they aim to discern spoofing attacks from bona fide speech trials.
ReMASC: Realistic Replay Attack Corpus for Voice Controlled Systems
This paper introduces a new database of voice recordings with the goal of supporting research on vulnerabilities and protection of voice-controlled systems (VCSs).
Spoof detection using time-delay shallow neural network and feature switching
mariganeshkumar/TDSNN-spoof-detection
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When combined with the decision-level feature switching (DLFS) paradigm, the best TD-SNN system outperforms the best baseline GMM system on evaluation data with a relative improvement of 48. 03\% and 49. 47\% for both logical and physical access, respectively.
Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing
Whether it be for results summarization, or the analysis of classifier fusion, some means to compare different classifiers can often provide illuminating insight into their behaviour, (dis)similarity or complementarity.
Efficient Attention Branch Network with Combined Loss Function for Automatic Speaker Verification Spoof Detection
AmirmohammadRostami/ASV-anti-spoofing-with-EABN
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Many endeavors have sought to develop countermeasure techniques as enhancements on Automatic Speaker Verification (ASV) systems, in order to make them more robust against spoof attacks.
FastAudio: A Learnable Audio Front-End for Spoof Speech Detection
magnumresearchgroup/Fastaudio
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The FastAudio front-end achieves a relative improvement of 27% when compared with fixed front-ends, outperforming all other learnable front-ends on this task.
AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks
clovaai/aasist
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Artefacts that differentiate spoofed from bona-fide utterances can reside in spectral or temporal domains.
RawBoost: A Raw Data Boosting and Augmentation Method applied to Automatic Speaker Verification Anti-Spoofing
TakHemlata/RawBoost-antispoofing
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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 inputs.
SAMO: Speaker Attractor Multi-Center One-Class Learning for Voice Anti-Spoofing
sivannavis/samo
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Our previous research on one-class learning has improved the generalization ability to unseen attacks by compacting the bona fide speech in the embedding space.
