no code implementations • 26 Sep 2023 • Hee-Soo Heo, Kihyun Nam, Bong-Jin Lee, Youngki Kwon, Minjae Lee, You Jin Kim, Joon Son Chung
In the field of speaker verification, session or channel variability poses a significant challenge.
no code implementations • 9 Nov 2022 • Youngki Kwon, Hee-Soo Heo, Bong-Jin Lee, You Jin Kim, Jee-weon Jung
Our focus lies in developing an online speaker diarisation framework which demonstrates robust performance across diverse domains.
no code implementations • 8 Nov 2022 • Hee-Soo Heo, Youngki Kwon, Bong-Jin Lee, You Jin Kim, Jee-weon Jung
Extracted dense frame-level embeddings can each represent a speaker.
no code implementations • 26 Oct 2022 • Jee-weon Jung, Hee-Soo Heo, Bong-Jin Lee, Jaesung Huh, Andrew Brown, Youngki Kwon, Shinji Watanabe, Joon Son Chung
First, the evaluation is not straightforward because the features required for better performance differ between speaker verification and diarisation.
no code implementations • 20 Oct 2022 • Jee-weon Jung, Hee-Soo Heo, Bong-Jin Lee, Jaesong Lee, Hye-jin Shim, Youngki Kwon, Joon Son Chung, Shinji Watanabe
We also show that training with proposed large data configurations gives better performance.
no code implementations • 28 Mar 2022 • Hee-Soo Heo, Jee-weon Jung, Jingu Kang, Youngki Kwon, You Jin Kim, Bong-Jin Lee, Joon Son Chung
The goal of this paper is to train effective self-supervised speaker representations without identity labels.
2 code implementations • 16 Mar 2022 • Jee-weon Jung, You Jin Kim, Hee-Soo Heo, Bong-Jin Lee, Youngki Kwon, Joon Son Chung
Our best model achieves an equal error rate of 0. 89%, which is competitive with the state-of-the-art models based on handcrafted features, and outperforms the best model based on raw waveform inputs by a large margin.
no code implementations • 7 Oct 2021 • Youngki Kwon, Hee-Soo Heo, Jee-weon Jung, You Jin Kim, Bong-Jin Lee, Joon Son Chung
The objective of this work is effective speaker diarisation using multi-scale speaker embeddings.
no code implementations • 7 Oct 2021 • You Jin Kim, Hee-Soo Heo, Jee-weon Jung, Youngki Kwon, Bong-Jin Lee, Joon Son Chung
The objective of this work is to train noise-robust speaker embeddings adapted for speaker diarisation.
1 code implementation • 17 Aug 2021 • You Jin Kim, Hee-Soo Heo, Soyeon Choe, Soo-Whan Chung, Yoohwan Kwon, Bong-Jin Lee, Youngki Kwon, Joon Son Chung
Face tracks are extracted from the videos and active segments are annotated based on the timestamps of VoxConverse in a semi-automatic way.
no code implementations • 7 Apr 2021 • Youngki Kwon, Jee-weon Jung, Hee-Soo Heo, You Jin Kim, Bong-Jin Lee, Joon Son Chung
The goal of this paper is to adapt speaker embeddings for solving the problem of speaker diarisation.
no code implementations • 7 Apr 2021 • Jee-weon Jung, Hee-Soo Heo, Youngki Kwon, Joon Son Chung, Bong-Jin Lee
In this work, we propose an overlapped speech detection system trained as a three-class classifier.