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Found 8 papers, 2 papers with code
ATMM-SAGA: Alternating Training for Multi-Module with Score-Aware Gated Attention SASV system
The objective of automatic speaker verification (ASV) systems is to determine whether a given test speech utterance corresponds to a claimed enrolled speaker.
ASVspoof2019 vs. ASVspoof5: Assessment and Comparison
ASVspoof challenges are designed to advance the understanding of spoofing speech attacks and encourage the development of robust countermeasure systems.
Tandem spoofing-robust automatic speaker verification based on time-domain embeddings
We propose a countermeasure (CM) system that employs time-domain embeddings derived from the PMF of spoofed and genuine speech, as well as gender recognition based on male and female time-based embeddings.
Ranked #1 on
Speaker Verification
on ASVspoof 2019 - LA
Spoofing-Robust Speaker Verification Based on Time-Domain Embedding
The CM system demonstrated an equal error rate (EER) of 9. 2% on the evaluation set for the male gender, with an EER of 10. 1% for the female gender.
Ranked #1 on
Voice Anti-spoofing
on ASVspoof 2019 - LA
(minDCF metric)
a-DCF: an architecture agnostic metric with application to spoofing-robust speaker verification
Spoofing detection is today a mainstream research topic.
Stochastic mean-shift clustering
In this paper we presented a stochastic version mean-shift clustering algorithm.
Thech. Report: Genuinization of Speech waveform PMF for speaker detection spoofing and countermeasures
In this article, we propose an algorithm, denoted genuinization, capable of reducing the waveform distribution gap between authentic speech and spoofing speech.
Time-Domain Based Embeddings for Spoofed Audio Representation
The main focus of this paper is to suggest new representations for genuine and spoofed speech, based on the probability mass function (PMF) estimation of the audio waveforms' amplitude.
