1 citations · 4 across the 15 of their papers we have counts for
15 papers
Improving Text-to-Music Generation with Human Preference Rewards
Yonghyun Kim, Junwon Lee, Haiwen Xia +2
We describe our entry to the efficiency track of the Academic Text-to-Music (ATTM) Grand Challenge at ICME 2026. Beyond the challenge protocol's FAD-CLAP and CLAP score, we add a l…
TuneJury: An Open Metric for Improving Music Generation Preference Alignment
Yonghyun Kim, Junwon Lee, Haiwen Xia +5
We introduce TuneJury, an open, instance-level pairwise reward model for text-to-music that predicts a music preference score from a text prompt and an audio clip. The released che…
AdaTT: Text-Guided Instrument Timbre Transfer with Target-Adaptive Structural Control
Dabin Kim, Junwon Lee, Juhan Nam
This paper addresses timbral ambiguity in instrument timbre transfer under fine-grained structural conditions. We argue this issue stems from instrument-specific expressive details…
CounterFlow: A Two-Phase Inference-Time Sampling for Counterfactual Video Foley Generation
Gyubin Lee, Junwon Lee, Juhan Nam
We investigate Counterfactual Video Foley Generation, which aims to adopt a sound-source identity that contradicts the visual evidence while remaining temporally synchronized to a…
UNMIXX: Untangling Highly Correlated Singing Voices Mixtures
Jihoo Jung, Ji-Hoon Kim, Doyeop Kwak +3
We introduce UNMIXX, a novel framework for multiple singing voices separation (MSVS). While related to speech separation, MSVS faces unique challenges: data scarcity and the highly…
Hear What Matters! Text-conditioned Selective Video-to-Audio Generation
Junwon Lee, Juhan Nam, Jiyoung Lee
This work introduces a new task, text-conditioned selective video-to-audio (V2A) generation, which produces only the user-intended sound from a multi-object video. This capability…
KAD: No More FAD! An Effective and Efficient Evaluation Metric for Audio Generation
Yoonjin Chung, Pilsun Eu, Junwon Lee +3
Although being widely adopted for evaluating generated audio signals, the Fréchet Audio Distance (FAD) suffers from significant limitations, including reliance on Gaussian assumpti…
Sound Scene Synthesis at the DCASE 2024 Challenge
Mathieu Lagrange, Junwon Lee, Modan Tailleur +5
This paper presents Task 7 at the DCASE 2024 Challenge: sound scene synthesis. Recent advances in sound synthesis and generative models have enabled the creation of realistic and d…
Challenge on Sound Scene Synthesis: Evaluating Text-to-Audio Generation
Junwon Lee, Modan Tailleur, Laurie M. Heller +5
Despite significant advancements in neural text-to-audio generation, challenges persist in controllability and evaluation. This paper addresses these issues through the Sound Scene…
Video-Foley: Two-Stage Video-To-Sound Generation via Temporal Event Condition For Foley Sound
Junwon Lee, Jaekwon Im, Dabin Kim +1
Foley sound synthesis is crucial for multimedia production, enhancing user experience by synchronizing audio and video both temporally and semantically. Recent studies on automatin…
CONMOD: Controllable Neural Frame-based Modulation Effects
Gyubin Lee, Hounsu Kim, Junwon Lee +1
Deep learning models have seen widespread use in modelling LFO-driven audio effects, such as phaser and flanger. Although existing neural architectures exhibit high-quality emulati…
Correlation of Fréchet Audio Distance With Human Perception of Environmental Audio Is Embedding Dependant
Modan Tailleur, Junwon Lee, Mathieu Lagrange +4
This paper explores whether considering alternative domain-specific embeddings to calculate the Fréchet Audio Distance (FAD) metric can help the FAD to correlate better with percep…
T-FOLEY: A Controllable Waveform-Domain Diffusion Model for Temporal-Event-Guided Foley Sound Synthesis
Yoonjin Chung, Junwon Lee, Juhan Nam
Foley sound, audio content inserted synchronously with videos, plays a critical role in the user experience of multimedia content. Recently, there has been active research in Foley…
Music Playlist Title Generation Using Artist Information
Haven Kim, SeungHeon Doh, Junwon Lee +1
Automatically generating or captioning music playlist titles given a set of tracks is of significant interest in music streaming services as customized playlists are widely used in…
Music Playlist Title Generation: A Machine-Translation Approach
SeungHeon Doh, Junwon Lee, Juhan Nam
We propose a machine-translation approach to automatically generate a playlist title from a set of music tracks. We take a sequence of track IDs as input and a sequence of words in…