15 citations · 22 across the 10 of their papers we have counts for
10 papers
EEND-DEMUX: End-to-End Neural Speaker Diarization via Demultiplexed Speaker Embeddings
Sung Hwan Mun, Min Hyun Han, Canyeong Moon +1
In recent years, there have been studies to further improve the end-to-end neural speaker diarization (EEND) systems. This letter proposes the EEND-DEMUX model, a novel framework u…
Towards single integrated spoofing-aware speaker verification embeddings
Sung Hwan Mun, Hye-jin Shim, Hemlata Tak +12
This study aims to develop a single integrated spoofing-aware speaker verification (SASV) embeddings that satisfy two aspects. First, rejecting non-target speakers' input as well a…
Adversarial Speaker-Consistency Learning Using Untranscribed Speech Data for Zero-Shot Multi-Speaker Text-to-Speech
Byoung Jin Choi, Myeonghun Jeong, Minchan Kim +2
Several recently proposed text-to-speech (TTS) models achieved to generate the speech samples with the human-level quality in the single-speaker and multi-speaker TTS scenarios wit…
Fully Unsupervised Training of Few-shot Keyword Spotting
Dongjune Lee, Minchan Kim, Sung Hwan Mun +2
For training a few-shot keyword spotting (FS-KWS) model, a large labeled dataset containing massive target keywords has known to be essential to generalize to arbitrary target keyw…
Disentangled Speaker Representation Learning via Mutual Information Minimization
Sung Hwan Mun, Min Hyun Han, Minchan Kim +2
Domain mismatch problem caused by speaker-unrelated feature has been a major topic in speaker recognition. In this paper, we propose an explicit disentanglement framework to unrave…
Frequency and Multi-Scale Selective Kernel Attention for Speaker Verification
Sung Hwan Mun, Jee-weon Jung, Min Hyun Han +1
The majority of recent state-of-the-art speaker verification architectures adopt multi-scale processing and frequency-channel attention mechanisms. Convolutional layers of these mo…
Bootstrap Equilibrium and Probabilistic Speaker Representation Learning for Self-supervised Speaker Verification
Sung Hwan Mun, Min Hyun Han, Dongjune Lee +2
In this paper, we propose self-supervised speaker representation learning strategies, which comprise of a bootstrap equilibrium speaker representation learning in the front-end and…
Unsupervised Representation Learning for Speaker Recognition via Contrastive Equilibrium Learning
Sung Hwan Mun, Woo Hyun Kang, Min Hyun Han +1
In this paper, we propose a simple but powerful unsupervised learning method for speaker recognition, namely Contrastive Equilibrium Learning (CEL), which increases the uncertainty…
Robust Text-Dependent Speaker Verification via Character-Level Information Preservation for the SdSV Challenge 2020
Sung Hwan Mun, Woo Hyun Kang, Min Hyun Han +1
This paper describes our submission to Task 1 of the Short-duration Speaker Verification (SdSV) challenge 2020. Task 1 is a text-dependent speaker verification task, where both the…
Disentangled speaker and nuisance attribute embedding for robust speaker verification
Woo Hyun Kang, Sung Hwan Mun, Min Hyun Han +1
Over the recent years, various deep learning-based embedding methods have been proposed and have shown impressive performance in speaker verification. However, as in most of the cl…