306 citations
- Finland UniversityFI46 papers
- Aalto UniversityFI10 papers
- Centre National de la Recherche ScientifiqueFR9 papers
- Tampere UniversityFI9 papers
- EURECOMFR5 papers
- Karlsruhe Institute of TechnologyDE5 papers
- National Institute of InformaticsJP5 papers
- University of HelsinkiFI5 papers
- Athinoula A. Martinos Center for Biomedical ImagingUS4 papers
- Harbin Engineering UniversityCN4 papers
- Harvard UniversityUS4 papers
- Institute for Infocomm ResearchSG4 papers
6 papers · 1 filter
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…
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…
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…
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…
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…