b'Hee-Soo Heo'

research

∙ 06/01/2023

Encoder-decoder multimodal speaker change detection

The task of speaker change detection (SCD), which detects points where s...

0 Jee-weon Jung, et al. ∙

research

∙ 11/09/2022

Absolute decision corrupts absolutely: conservative online speaker diarisation

Our focus lies in developing an online speaker diarisation framework whi...

0 Youngki Kwon, et al. ∙

research

∙ 11/08/2022

High-resolution embedding extractor for speaker diarisation

Speaker embedding extractors significantly influence the performance of ...

0 Hee-Soo Heo, et al. ∙

research

∙ 11/01/2022

Disentangled representation learning for multilingual speaker recognition

The goal of this paper is to train speaker embeddings that are robust to...

0 Kihyun Nam, et al. ∙

research

∙ 10/20/2022

Large-scale learning of generalised representations for speaker recognition

The objective of this work is to develop a speaker recognition model to ...

0 Jee-weon Jung, et al. ∙

research

∙ 04/21/2022

Baseline Systems for the First Spoofing-Aware Speaker Verification Challenge: Score and Embedding Fusion

Deep learning has brought impressive progress in the study of both autom...

0 Hye-Jin Shim, et al. ∙

research

∙ 03/16/2022

Raw waveform speaker verification for supervised and self-supervised learning

Speaker verification models that directly operate upon raw waveforms are...

0 Jee-weon Jung, et al. ∙

research

∙ 01/25/2022

SASV Challenge 2022: A Spoofing Aware Speaker Verification Challenge Evaluation Plan

ASV (automatic speaker verification) systems are intrinsically required ...

0 Jee-weon Jung, et al. ∙

research

∙ 10/07/2021

Disentangled dimensionality reduction for noise-robust speaker diarisation

The objective of this work is to train noise-robust speaker embeddings f...

0 You Jin Kim, et al. ∙

research

∙ 10/07/2021

Multi-scale speaker embedding-based graph attention networks for speaker diarisation

The objective of this work is effective speaker diarisation using multi-...

0 Youngki Kwon, et al. ∙

research

∙ 10/04/2021

AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks

Artefacts that differentiate spoofed from bona-fide utterances can resid...

0 Jee-weon Jung, et al. ∙

research

∙ 08/17/2021

Look Who's Talking: Active Speaker Detection in the Wild

In this work, we present a novel audio-visual dataset for active speaker...

0 You Jin Kim, et al. ∙

research

∙ 04/07/2021

Adapting Speaker Embeddings for Speaker Diarisation

The goal of this paper is to adapt speaker embeddings for solving the pr...

0 Youngki Kwon, et al. ∙

research

∙ 04/07/2021

Three-class Overlapped Speech Detection using a Convolutional Recurrent Neural Network

In this work, we propose an overlapped speech detection system trained a...

0 Jee-weon Jung, et al. ∙

research

∙ 11/30/2020

Look who's not talking

The objective of this work is speaker diarisation of speech recordings '...

0 Youngki Kwon, et al. ∙

research

∙ 10/29/2020

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

The VoxCeleb Speaker Recognition Challenge (VoxSRC) at Interspeech 2020 ...

0 Yoohwan Kwon, et al. ∙

research

∙ 10/22/2020

Graph Attention Networks for Speaker Verification

This work presents a novel back-end framework for speaker verification u...

0 Jee-weon Jung, et al. ∙

research

∙ 09/29/2020

Clova Baseline System for the VoxCeleb Speaker Recognition Challenge 2020

This report describes our submission to the VoxCeleb Speaker Recognition...

0 Hee-Soo Heo, et al. ∙

research

∙ 07/23/2020

Augmentation adversarial training for unsupervised speaker recognition

The goal of this work is to train robust speaker recognition models with...

0 Jaesung Huh, et al. ∙

research

∙ 05/18/2020

End-to-End Lip Synchronisation

The goal of this work is to synchronise audio and video of a talking fac...

0 You Jin Kim, et al. ∙

research

∙ 03/26/2020

In defence of metric learning for speaker recognition

The objective of this paper is 'open-set' speaker recognition of unseen ...

0 Joon Son Chung, et al. ∙

research

∙ 01/31/2020

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

In this study, we analyze the role of various categories of subsidiary i...

0 Jee-weon Jung, et al. ∙

research

∙ 10/22/2019

Self-supervised pre-training with acoustic configurations for replay spoofing detection

Large datasets are well-known as a key to the recent advances in deep le...

0 Hye-Jin Shim, et al. ∙

research

∙ 07/01/2019

Cosine similarity-based adversarial process

An adversarial process between two deep neural networks is a promising a...

0 Hee-Soo Heo, et al. ∙

research

∙ 04/23/2019

Acoustic scene classification using teacher-student learning with soft-labels

Acoustic scene classification identifies an input segment into one of th...

0 Hee-Soo Heo, et al. ∙

research

∙ 04/23/2019

Replay attack detection with complementary high-resolution information using end-to-end DNN for the ASVspoof 2019 Challenge

In this study, we concentrate on replacing the process of extracting han...

0 Jee-weon Jung, et al. ∙

research

∙ 04/17/2019

RawNet: Advanced end-to-end deep neural network using raw waveforms for text-independent speaker verification

Recently, direct modeling of raw waveforms using deep neural networks ha...

0 Jee-weon Jung, et al. ∙

research

∙ 02/07/2019

End-to-end losses based on speaker basis vectors and all-speaker hard negative mining for speaker verification

In recent years, speaker verification has been primarily performed using...

0 Hee-Soo Heo, et al. ∙

research

∙ 10/25/2018

Short utterance compensation in speaker verification via cosine-based teacher-student learning of speaker embeddings

Input utterance with short duration is one of the most critical threats ...

0 Jee-weon Jung, et al. ∙

research

∙ 08/29/2018

Replay spoofing detection system for automatic speaker verification using multi-task learning of noise classes

In this paper, we propose a replay attack spoofing detection system for ...

0 Hye-Jin Shim, et al. ∙

Hee-Soo Heo

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