no code implementations • 20 Nov 2023 • Jungil Kong, Junmo Lee, Jeongmin Kim, Beomjeong Kim, Jihoon Park, Dohee Kong, Changheon Lee, Sangjin Kim
To overcome previous limitations, we propose effective methods for feature learning and representing target speakers' speech characteristics by discretizing the features and conditioning them to a speech synthesis model.
1 code implementation • 22 Aug 2023 • JungHoon Kim, Yeonjun In, Kanghoon Yoon, Junmo Lee, Chanyoung Park
Unsupervised GAD methods assume the lack of anomaly labels, i. e., whether a node is anomalous or not.
no code implementations • 6 May 2023 • SangHyeon Park, Junmo Lee, Soo-Mook Moon
Decentralized solutions such as blockchain have been proposed to tackle these issues, but they often struggle when dealing with large-scale models, leading to time-consuming inference and inefficient training verification.
2 code implementations • 27 Jun 2022 • Taejun Bak, Junmo Lee, Hanbin Bae, Jinhyeok Yang, Jae-Sung Bae, Young-Sun Joo
Therefore, in this paper, we investigate the relationship between these artifacts and GAN-based vocoders and propose a GAN-based vocoder, called Avocodo, that allows the synthesis of high-fidelity speech with reduced artifacts.