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20212023
most citedNeural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations

13 citations · 26 across the 11 of their papers we have counts for

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cs.SD2023

Exploiting Time-Frequency Conformers for Music Audio Enhancement

Yunkee Chae, Junghyun Koo, Sungho Lee +1

With the proliferation of video platforms on the internet, recording musical performances by mobile devices has become commonplace. However, these recordings often suffer from degr…

cs.SD2023

Music De-limiter Networks via Sample-wise Gain Inversion

Chang-Bin Jeon, Kyogu Lee

The loudness war, an ongoing phenomenon in the music industry characterized by the increasing final loudness of music while reducing its dynamic range, has been a controversial top…

cs.SD2023

Blind Estimation of Audio Processing Graph

Sungho Lee, Jaehyun Park, Seungryeol Paik +1

Musicians and audio engineers sculpt and transform their sounds by connecting multiple processors, forming an audio processing graph. However, most deep-learning methods overlook t…

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.SD2022★ 4 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…

cs.SD2021★ 13 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…