Search Results for author: Mitchell McLaren

Found 10 papers, 4 papers with code

Joint PLDA for Simultaneous Modeling of Two Factors

no code implementations28 Mar 2018 Luciana Ferrer, Mitchell McLaren

The approach does not change the basic form of PLDA but rather modifies the training procedure to consider the dependency across samples of the latent variable that models within-class variability.

Face Recognition Speaker Verification +1

Semi-supervised acoustic model training for speech with code-switching

no code implementations23 Oct 2018 Emre Yilmaz, Mitchell McLaren, Henk van den Heuvel, David A. van Leeuwen

In this paper, we describe several automatic annotation approaches to enable using of a large amount of raw bilingual broadcast data for acoustic model training in a semi-supervised setting.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

The VOiCES from a Distance Challenge 2019 Evaluation Plan

3 code implementations27 Feb 2019 Mahesh Kumar Nandwana, Julien van Hout, Mitchell McLaren, Colleen Richey, Aaron Lawson, Maria Alejandra Barrios

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 single channel distant/far-field audio, under noisy conditions.

Audio and Speech Processing Sound

A discriminative condition-aware backend for speaker verification

no code implementations26 Nov 2019 Luciana Ferrer, Mitchell McLaren

However, unlike the standard backends, all parameters of the model are jointly trained to optimize the binary cross-entropy for the speaker verification task.

Speaker Verification

VoxSRC 2019: The first VoxCeleb Speaker Recognition Challenge

no code implementations5 Dec 2019 Joon Son Chung, Arsha Nagrani, Ernesto Coto, Weidi Xie, Mitchell McLaren, Douglas A. Reynolds, Andrew Zisserman

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.

Speaker Recognition

A Speaker Verification Backend for Improved Calibration Performance across Varying Conditions

2 code implementations5 Feb 2020 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 varying levels of mismatch to the training conditions.

Speaker Verification

A Speaker Verification Backend with Robust Performance across Conditions

1 code implementation2 Feb 2021 Luciana Ferrer, Mitchell McLaren, Niko Brummer

When trained on a number of diverse datasets that are labeled only with respect to speaker, the proposed backend consistently and, in some cases, dramatically improves calibration, compared to the standard PLDA approach, on a number of held-out datasets, some of which are markedly different from the training data.

Speaker Verification

A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognition

1 code implementation4 Jan 2022 Luciana Ferrer, Diego Castan, Mitchell McLaren, Aaron Lawson

We show that this hierarchical approach consistently outperforms the non-hierarchical one for detection of highly related languages, in many cases by large margins.

Machine Translation speech-recognition +1

Cannot find the paper you are looking for? You can Submit a new open access paper.