175 citations · 328 across the 12 of their papers we have counts for
14 papers
ASVspoof 2019: spoofing countermeasures for the detection of synthesized, converted and replayed speech
Andreas Nautsch, Xin Wang, Nicholas Evans +7
The ASVspoof initiative was conceived to spearhead research in anti-spoofing for automatic speaker verification (ASV). This paper describes the third in a series of bi-annual chall…
Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentals
Tomi Kinnunen, Héctor Delgado, Nicholas Evans +8
Recent years have seen growing efforts to develop spoofing countermeasures (CMs) to protect automatic speaker verification (ASV) systems from being deceived by manipulated or artif…
Extrapolating false alarm rates in automatic speaker verification
Alexey Sholokhov, Tomi Kinnunen, Ville Vestman +1
Automatic speaker verification (ASV) vendors and corpus providers would both benefit from tools to reliably extrapolate performance metrics for large speaker populations without co…
UIAI System for Short-Duration Speaker Verification Challenge 2020
Md Sahidullah, Achintya Kumar Sarkar, Ville Vestman +5
In this work, we present the system description of the UIAI entry for the short-duration speaker verification (SdSV) challenge 2020. Our focus is on Task 1 dedicated to text-depend…
Neural i-vectors
Ville Vestman, Kong Aik Lee, Tomi H. Kinnunen
Deep speaker embeddings have been demonstrated to outperform their generative counterparts, i-vectors, in recent speaker verification evaluations. To combine the benefits of high p…
Voice Biometrics Security: Extrapolating False Alarm Rate via Hierarchical Bayesian Modeling of Speaker Verification Scores
Alexey Sholokhov, Tomi Kinnunen, Ville Vestman +1
How secure automatic speaker verification (ASV) technology is? More concretely, given a specific target speaker, how likely is it to find another person who gets falsely accepted a…
ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech
Xin Wang, Junichi Yamagishi, Massimiliano Todisco +37
Automatic speaker verification (ASV) is one of the most natural and convenient means of biometric person recognition. Unfortunately, just like all other biometric systems, ASV is v…
Unleashing the Unused Potential of I-Vectors Enabled by GPU Acceleration
Ville Vestman, Kong Aik Lee, Tomi H. Kinnunen +1
Speaker embeddings are continuous-value vector representations that allow easy comparison between voices of speakers with simple geometric operations. Among others, i-vector and x-…
Voice Mimicry Attacks Assisted by Automatic Speaker Verification
Ville Vestman, Tomi Kinnunen, Rosa González Hautamäki +1
In this work, we simulate a scenario, where a publicly available ASV system is used to enhance mimicry attacks against another closed source ASV system. In specific, ASV technology…
I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences
Kong Aik Lee, Ville Hautamaki, Tomi Kinnunen +43
The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which…
ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection
Massimiliano Todisco, Xin Wang, Ville Vestman +7
ASVspoof, now in its third edition, is a series of community-led challenges which promote the development of countermeasures to protect automatic speaker verification (ASV) from th…
Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection
Tomi Kinnunen, Rosa González Hautamäki, Ville Vestman +1
We consider technology-assisted mimicry attacks in the context of automatic speaker verification (ASV). We use ASV itself to select targeted speakers to be attacked by human-based…
Who Do I Sound Like? Showcasing Speaker Recognition Technology by YouTube Voice Search
Ville Vestman, Bilal Soomro, Anssi Kanervisto +2
The popularization of science can often be disregarded by scientists as it may be challenging to put highly sophisticated research into words that general public can understand. Th…
Supervector Compression Strategies to Speed up I-Vector System Development
Ville Vestman, Tomi Kinnunen
The front-end factor analysis (FEFA), an extension of principal component analysis (PPCA) tailored to be used with Gaussian mixture models (GMMs), is currently the prevalent approa…