most citedNeural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations

13 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2022

Show Me the Instruments: Musical Instrument Retrieval from Mixture Audio

Kyungsu Kim, Minju Park, Haesun Joung +4

As digital music production has become mainstream, the selection of appropriate virtual instruments plays a crucial role in determining the quality of music. To search the musical…

cs.SD20224 cited

Expressive Singing Synthesis Using Local Style Token and Dual-path Pitch Encoder

Juheon Lee, Hyeong-Seok Choi, Kyogu Lee

This paper proposes a controllable singing voice synthesis system capable of generating expressive singing voice with two novel methodologies. First, a local style token module, wh…

eess.AS2022

End-to-end Music Remastering System Using Self-supervised and Adversarial Training

Junghyun Koo, Seungryeol Paik, Kyogu Lee

Mastering is an essential step in music production, but it is also a challenging task that has to go through the hands of experienced audio engineers, where they adjust tone, space…

cs.SD202113 cited

Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations

Hyeong-Seok Choi, Juheon Lee, Wansoo Kim +3

We present a neural analysis and synthesis (NANSY) framework that can manipulate voice, pitch, and speed of an arbitrary speech signal. Most of the previous works have focused on u…

cs.SD2021

Cross-domain Semi-Supervised Audio Event Classification Using Contrastive Regularization

Donmoon Lee, Kyogu Lee

In this study, we proposed a novel semi-supervised training method that uses unlabeled data with a class distribution that is completely different from the target data or data with…