5 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…
Music Arena: Live Evaluation for Text-to-Music
Yonghyun Kim, Wayne Chi, Anastasios N. Angelopoulos +5
We present Music Arena, an open platform for scalable human preference evaluation of text-to-music (TTM) models. Soliciting human preferences via listening studies is the gold stan…
NeoLightning: A Modern Reimagination of Gesture-Based Sound Design
Yonghyun Kim, Sangheon Park, Marcus Parker +2
This paper introduces NeoLightning, a modern reinterpretation of the Buchla Lightning. NeoLightning preserves the innovative spirit of Don Buchla's "Buchla Lightning" (introduced i…
Towards Robust Transcription: Exploring Noise Injection Strategies for Training Data Augmentation
Yonghyun Kim, Alexander Lerch
Recent advancements in Automatic Piano Transcription (APT) have significantly improved system performance, but the impact of noisy environments on the system performance remains la…