5 papers · 1 filter
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…
Schrödinger Bridge Consistency Trajectory Models for Speech Enhancement
Shuichiro Nishigori, Koichi Saito, Naoki Murata +3
Speech enhancement (SE) utilizing diffusion models is a promising technology that improves speech quality in noisy speech data. Furthermore, the Schrödinger bridge (SB) has recentl…
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…
Aligning Text-to-Music Evaluation with Human Preferences
Yichen Huang, Zachary Novack, Koichi Saito +5
Despite significant recent advances in generative acoustic text-to-music (TTM) modeling, robust evaluation of these models lags behind, relying in particular on the popular Fréchet…
VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music
Jiatong Shi, Hye-jin Shim, Jinchuan Tian +14
In this work, we introduce VERSA, a unified and standardized evaluation toolkit designed for various speech, audio, and music signals. The toolkit features a Pythonic interface wit…