activity
20182026
most citedIn defence of metric learning for speaker recognition

399 citations · 591 across the 32 of their papers we have counts for

collaborators
Showing 2020Show all

10 papers · 1 filter

cs.SD2020

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…

eess.AS2020

Learning in your voice: Non-parallel voice conversion based on speaker consistency loss

Yoohwan Kwon, Soo-Whan Chung, Hee-Soo Heo +1

In this paper, we propose a novel voice conversion strategy to resolve the mismatch between the training and conversion scenarios when parallel speech corpus is unavailable for tra…

cs.SD2020

The ins and outs of speaker recognition: lessons from VoxSRC 2020

Yoohwan Kwon, Hee-Soo Heo, Bong-Jin Lee +1

The VoxCeleb Speaker Recognition Challenge (VoxSRC) at Interspeech 2020 offers a challenging evaluation for speaker recognition systems, which includes celebrities playing differen…

eess.AS2020

Graph Attention Networks for Speaker Verification

Jee-weon Jung, Hee-Soo Heo, Ha-Jin Yu +1

This work presents a novel back-end framework for speaker verification using graph attention networks. Segment-wise speaker embeddings extracted from multiple crops within an utter…

eess.AS2020★ 97 cited

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…

cs.SD2020★ 12 cited

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…

eess.AS2020

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…

cs.CV2020

End-to-End Lip Synchronisation Based on Pattern Classification

You Jin Kim, Hee Soo Heo, Soo-Whan Chung +1

The goal of this work is to synchronise audio and video of a talking face using deep neural network models. Existing works have trained networks on proxy tasks such as cross-modal…

eess.AS2020★ 399 cited

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…

eess.AS2020★ 2 cited

A study on the role of subsidiary information in replay attack spoofing detection

Jee-weon Jung, Hye-jin Shim, Hee-Soo Heo +1

In this study, we analyze the role of various categories of subsidiary information in conducting replay attack spoofing detection: `Room Size', `Reverberation', `Speaker-to-ASV dis…