22 citations · 35 across the 14 of their papers we have counts for
9 papers · 1 filter
SEED: Speaker Embedding Enhancement Diffusion Model
KiHyun Nam, Jungwoo Heo, Jee-weon Jung +4
A primary challenge when deploying speaker recognition systems in real-world applications is performance degradation caused by environmental mismatch. We propose a diffusion-based…
To what extent can ASV systems naturally defend against spoofing attacks?
Jee-weon Jung, Xin Wang, Nicholas Evans +6
The current automatic speaker verification (ASV) task involves making binary decisions on two types of trials: target and non-target. However, emerging advancements in speech gener…
Rethinking Session Variability: Leveraging Session Embeddings for Session Robustness in Speaker Verification
Hee-Soo Heo, KiHyun Nam, Bong-Jin Lee +4
In the field of speaker verification, session or channel variability poses a significant challenge. While many contemporary methods aim to disentangle session information from spea…
Metric Learning for User-defined Keyword Spotting
Jaemin Jung, Youkyum Kim, Jihwan Park +4
The goal of this work is to detect new spoken terms defined by users. While most previous works address Keyword Spotting (KWS) as a closed-set classification problem, this limits t…
Pushing the limits of raw waveform speaker recognition
Jee-weon Jung, You Jin Kim, Hee-Soo Heo +3
In recent years, speaker recognition systems based on raw waveform inputs have received increasing attention. However, the performance of such systems are typically inferior to the…
Multi-scale speaker embedding-based graph attention networks for speaker diarisation
Youngki Kwon, Hee-Soo Heo, Jee-weon Jung +3
The objective of this work is effective speaker diarisation using multi-scale speaker embeddings. Typically, there is a trade-off between the ability to recognise short speaker seg…