175 citations · 709 across the 60 of their papers we have counts for
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Multi-Dataset Co-Training with Sharpness-Aware Optimization for Audio Anti-spoofing
Hye-jin Shim, Jee-weon Jung, Tomi Kinnunen
Audio anti-spoofing for automatic speaker verification aims to safeguard users' identities from spoofing attacks. Although state-of-the-art spoofing countermeasure(CM) models perfo…
Speaker-Aware Anti-Spoofing
Xuechen Liu, Md Sahidullah, Kong Aik Lee +1
We address speaker-aware anti-spoofing, where prior knowledge of the target speaker is incorporated into a voice spoofing countermeasure (CM). In contrast to the frequently used sp…
Distilling Multi-Level X-vector Knowledge for Small-footprint Speaker Verification
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
Even though deep speaker models have demonstrated impressive accuracy in speaker verification tasks, this often comes at the expense of increased model size and computation time, p…
ASVspoof 2021: Towards Spoofed and Deepfake Speech Detection in the Wild
Xuechen Liu, Xin Wang, Md Sahidullah +8
Benchmarking initiatives support the meaningful comparison of competing solutions to prominent problems in speech and language processing. Successive benchmarking evaluations typic…
Gamified Speaker Comparison by Listening
Sandip Ghimire, Tomi Kinnunen, Rosa Gonzalez Hautamäki
We address speaker comparison by listening in a game-like environment, hypothesized to make the task more motivating for naive listeners. We present the same 30 trials selected wit…
Spoofing-Aware Speaker Verification with Unsupervised Domain Adaptation
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
In this paper, we initiate the concern of enhancing the spoofing robustness of the automatic speaker verification (ASV) system, without the primary presence of a separate counterme…
Baseline Systems for the First Spoofing-Aware Speaker Verification Challenge: Score and Embedding Fusion
Hye-jin Shim, Hemlata Tak, Xuechen Liu +12
Deep learning has brought impressive progress in the study of both automatic speaker verification (ASV) and spoofing countermeasures (CM). Although solutions are mutually dependent…
Improving speaker de-identification with functional data analysis of f0 trajectories
Lauri Tavi, Tomi Kinnunen, Rosa González Hautamäki
Due to a constantly increasing amount of speech data that is stored in different types of databases, voice privacy has become a major concern. To respond to such concern, speech re…
SASV Challenge 2022: A Spoofing Aware Speaker Verification Challenge Evaluation Plan
Jee-weon Jung, Hemlata Tak, Hye-jin Shim +7
ASV (automatic speaker verification) systems are intrinsically required to reject both non-target (e.g., voice uttered by different speaker) and spoofed (e.g., synthesised or conve…
Learnable Nonlinear Compression for Robust Speaker Verification
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
In this study, we focus on nonlinear compression methods in spectral features for speaker verification based on deep neural network. We consider different kinds of channel-dependen…
Optimizing Tandem Speaker Verification and Anti-Spoofing Systems
Anssi Kanervisto, Ville Hautamäki, Tomi Kinnunen +1
As automatic speaker verification (ASV) systems are vulnerable to spoofing attacks, they are typically used in conjunction with spoofing countermeasure (CM) systems to improve secu…
Optimizing Multi-Taper Features for Deep Speaker Verification
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
Multi-taper estimators provide low-variance power spectrum estimates that can be used in place of the windowed discrete Fourier transform (DFT) to extract speech features such as m…
Optimized Power Normalized Cepstral Coefficients towards Robust Deep Speaker Verification
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
After their introduction to robust speech recognition, power normalized cepstral coefficient (PNCC) features were successfully adopted to other tasks, including speaker verificatio…
Parameterized Channel Normalization for Far-field Deep Speaker Verification
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
We address far-field speaker verification with deep neural network (DNN) based speaker embedding extractor, where mismatch between enrollment and test data often comes from convolu…
Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing
Tomi Kinnunen, Andreas Nautsch, Md Sahidullah +6
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 behavio…
Learnable MFCCs for Speaker Verification
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
We propose a learnable mel-frequency cepstral coefficient (MFCC) frontend architecture for deep neural network (DNN) based automatic speaker verification. Our architecture retains…
Introduction to Voice Presentation Attack Detection and Recent Advances
Md Sahidullah, Hector Delgado, Massimiliano Todisco +4
Over the past few years significant progress has been made in the field of presentation attack detection (PAD) for automatic speaker recognition (ASV). This includes the developmen…
Transforming acoustic characteristics to deceive playback spoofing countermeasures of speaker verification systems
Fuming Fang, Junichi Yamagishi, Isao Echizen +2
Automatic speaker verification (ASV) systems use a playback detector to filter out playback attacks and ensure verification reliability. Since current playback detection models are…
Perceptual Evaluation of the Effectiveness of Voice Disguise by Age Modification
Rosa González Hautamäki, Anssi Kanervisto, Ville Hautamäki +1
Voice disguise, purposeful modification of one's speaker identity with the aim of avoiding being identified as oneself, is a low-effort way to fool speaker recognition, whether per…
Spoofing Detection Goes Noisy: An Analysis of Synthetic Speech Detection in the Presence of Additive Noise
Cemal Hanilci, Tomi Kinnunen, Md Sahidullah +1
Automatic speaker verification (ASV) technology is recently finding its way to end-user applications for secure access to personal data, smart services or physical facilities. Simi…