activity
20192026
most citedRepresentation Selective Self-distillation and wav2vec 2.0 Feature Exploration for Spoof-aware Speaker Verification

15 citations · 24 across the 25 of their papers we have counts for

collaborators
Showing eess.ASShow all

9 papers · 1 filter

eess.AS2026

End-to-End Historical Music Restoration in Latent Space

Steven Cho, Junghyun Koo, Raphael Lafargue +3

Historical music restoration (HMR) has almost exclusively focused on constrained problems such as Super-Resolution or the restoration of solo pieces, under-exploring the general ta…

eess.AS2025

Automatic Music Mixing using a Generative Model of Effect Embeddings

Eloi Moliner, Marco A. Martínez-Ramírez, Junghyun Koo +5

Music mixing involves combining individual tracks into a cohesive mixture, a task characterized by subjectivity where multiple valid solutions exist for the same input. Existing au…

eess.AS2025

Towards Blind Data Cleaning: A Case Study in Music Source Separation

Azalea Gui, Woosung Choi, Junghyun Koo +5

The performance of deep learning models for music source separation heavily depends on training data quality. However, datasets are often corrupted by difficult-to-detect artifacts…

eess.AS2024

DDD: A Perceptually Superior Low-Response-Time DNN-based Declipper

Jayeon Yi, Junghyun Koo, Kyogu Lee

Clipping is a common nonlinear distortion that occurs whenever the input or output of an audio system exceeds the supported range. This phenomenon undermines not only the perceptio…

eess.AS2023★ 2 cited

Self-refining of Pseudo Labels for Music Source Separation with Noisy Labeled Data

Junghyun Koo, Yunkee Chae, Chang-Bin Jeon +1

Music source separation (MSS) faces challenges due to the limited availability of correctly-labeled individual instrument tracks. With the push to acquire larger datasets to improv…

eess.AS2022★ 1 cited

Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio Effects

Junghyun Koo, Marco A. Martínez-Ramírez, Wei-Hsiang Liao +3

We propose an end-to-end music mixing style transfer system that converts the mixing style of an input multitrack to that of a reference song. This is achieved with an encoder pre-…

eess.AS2022★ 15 cited

Representation Selective Self-distillation and wav2vec 2.0 Feature Exploration for Spoof-aware Speaker Verification

Jin Woo Lee, Eungbeom Kim, Junghyun Koo +1

Text-to-speech and voice conversion studies are constantly improving to the extent where they can produce synthetic speech almost indistinguishable from bona fide human speech. In…

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…

eess.AS2021★ 2 cited

Reverb Conversion of Mixed Vocal Tracks Using an End-to-end Convolutional Deep Neural Network

Junghyun Koo, Seungryeol Paik, Kyogu Lee

Reverb plays a critical role in music production, where it provides listeners with spatial realization, timbre, and texture of the music. Yet, it is challenging to reproduce the mu…