399 citations · 903 across the 21 of their papers we have counts for
9 papers · 1 filter
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…
Look who's not talking
Youngki Kwon, Hee Soo Heo, Jaesung Huh +2
The objective of this work is speaker diarisation of speech recordings 'in the wild'. The ability to determine speech segments is a crucial part of diarisation systems, accounting…
Playing a Part: Speaker Verification at the Movies
Andrew Brown, Jaesung Huh, Arsha Nagrani +2
The goal of this work is to investigate the performance of popular speaker recognition models on speech segments from movies, where often actors intentionally disguise their voice…
Clova Baseline System for the VoxCeleb Speaker Recognition Challenge 2020
Hee Soo Heo, Bong-Jin Lee, Jaesung Huh +1
This report describes our submission to the VoxCeleb Speaker Recognition Challenge (VoxSRC) at Interspeech 2020. We perform a careful analysis of speaker recognition models based o…
Augmentation adversarial training for self-supervised speaker recognition
Jaesung Huh, Hee Soo Heo, Jingu Kang +2
The goal of this work is to train robust speaker recognition models without speaker labels. Recent works on unsupervised speaker representations are based on contrastive learning i…
Spot the conversation: speaker diarisation in the wild
Joon Son Chung, Jaesung Huh, Arsha Nagrani +2
The goal of this paper is speaker diarisation of videos collected 'in the wild'. We make three key contributions. First, we propose an automatic audio-visual diarisation method for…
Metric Learning for Keyword Spotting
Jaesung Huh, Minjae Lee, Heesoo Heo +2
The goal of this work is to train effective representations for keyword spotting via metric learning. Most existing works address keyword spotting as a closed-set classification pr…
In defence of metric learning for speaker recognition
Joon Son Chung, Jaesung Huh, Seongkyu Mun +7
The objective of this paper is 'open-set' speaker recognition of unseen speakers, where ideal embeddings should be able to condense information into a compact utterance-level repre…
Modeling Musical Onset Probabilities via Neural Distribution Learning
Jaesung Huh, Egil Martinsson, Adrian Kim +1
Musical onset detection can be formulated as a time-to-event (TTE) or time-since-event (TSE) prediction task by defining music as a sequence of onset events. Here we propose a nove…