108 citations · 227 across the 6 of their papers we have counts for
7 papers
The NIST CTS Speaker Recognition Challenge
Seyed Omid Sadjadi, Craig Greenberg, Elliot Singer +2
The US National Institute of Standards and Technology (NIST) has been conducting a second iteration of the CTS challenge since August 2020. The current iteration of the CTS Challen…
VoxSRC 2020: The Second VoxCeleb Speaker Recognition Challenge
Arsha Nagrani, Joon Son Chung, Jaesung Huh +6
We held the second installment of the VoxCeleb Speaker Recognition Challenge in conjunction with Interspeech 2020. The goal of this challenge was to assess how well current speaker…
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…
VoxSRC 2019: The first VoxCeleb Speaker Recognition Challenge
Joon Son Chung, Arsha Nagrani, Ernesto Coto +4
The VoxCeleb Speaker Recognition Challenge 2019 aimed to assess how well current speaker recognition technology is able to identify speakers in unconstrained or `in the wild' data.…
MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation
Suwon Shon, Najim Dehak, Douglas Reynolds +1
The Multi-target Challenge aims to assess how well current speech technology is able to determine whether or not a recorded utterance was spoken by one of a large number of blackli…
t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification
Tomi Kinnunen, Kong Aik Lee, Hector Delgado +5
The ASVspoof challenge series was born to spearhead research in anti-spoofing for automatic speaker verification (ASV). The two challenge editions in 2015 and 2017 involved the ass…
A Unified Deep Neural Network for Speaker and Language Recognition
Fred Richardson, Douglas Reynolds, Najim Dehak
Learned feature representations and sub-phoneme posteriors from Deep Neural Networks (DNNs) have been used separately to produce significant performance gains for speaker and langu…