65 citations · 182 across the 10 of their papers we have counts for
11 papers
Detecting Synthetic Speech Manipulation in Real Audio Recordings
Md Hafizur Rahman, Martin Graciarena, Diego Castan +3
Recent advances in artificial speech and audio technologies have improved the abilities of deep-fake operators to falsify media and spread malicious misinformation. Anyone with lim…
A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognition
Luciana Ferrer, Diego Castan, Mitchell McLaren +1
Spoken language recognition (SLR) refers to the automatic process used to determine the language present in a speech sample. SLR is an important task in its own right, for example,…
A Speaker Verification Backend with Robust Performance across Conditions
Luciana Ferrer, Mitchell McLaren, Niko Brummer
In this paper, we address the problem of speaker verification in conditions unseen or unknown during development. A standard method for speaker verification consists of extracting…
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…
Temporarily-Aware Context Modelling using Generative Adversarial Networks for Speech Activity Detection
Tharindu Fernando, Sridha Sridharan, Mitchell McLaren +3
This paper presents a novel framework for Speech Activity Detection (SAD). Inspired by the recent success of multi-task learning approaches in the speech processing domain, we prop…
A Speaker Verification Backend for Improved Calibration Performance across Varying Conditions
Luciana Ferrer, Mitchell McLaren
In a recent work, we presented a discriminative backend for speaker verification that achieved good out-of-the-box calibration performance on most tested conditions containing vary…
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.…
A discriminative condition-aware backend for speaker verification
Luciana Ferrer, Mitchell McLaren
We present a scoring approach for speaker verification that mimics the standard PLDA-based backend process used in most current speaker verification systems. However, unlike the st…
The VOiCES from a Distance Challenge 2019 Evaluation Plan
Mahesh Kumar Nandwana, Julien van Hout, Mitchell McLaren +3
The "VOiCES from a Distance Challenge 2019" is designed to foster research in the area of speaker recognition and automatic speech recognition (ASR) with the special focus on singl…
Semi-supervised acoustic model training for speech with code-switching
Emre Yılmaz, Mitchell McLaren, Henk van den Heuvel +1
In the FAME! project, we aim to develop an automatic speech recognition (ASR) system for Frisian-Dutch code-switching (CS) speech extracted from the archives of a local broadcaster…
Joint PLDA for Simultaneous Modeling of Two Factors
Luciana Ferrer, Mitchell McLaren
Probabilistic linear discriminant analysis (PLDA) is a method used for biometric problems like speaker or face recognition that models the variability of the samples using two late…