9 papers
Voices of Civilizations: A Multilingual QA Benchmark for Global Music Understanding
Shangda Wu, Ziya Zhou, Yongyi Zang +4
We introduce Voices of Civilizations, the first multilingual QA benchmark for evaluating audio LLMs' cultural comprehension on full-length music recordings. Covering 380 tracks acr…
Summary of The Inaugural Music Source Restoration Challenge
Yongyi Zang, Jiarui Hai, Wanying Ge +5
Music Source Restoration (MSR) aims to recover original, unprocessed instrument stems from professionally mixed and degraded audio, requiring the reversal of both production effect…
MSRBench: A Benchmarking Dataset for Music Source Restoration
Yongyi Zang, Jiarui Hai, Wanying Ge +5
Music Source Restoration (MSR) extends source separation to realistic settings where signals undergo production effects (equalization, compression, reverb) and real-world degradati…
YuE: Scaling Open Foundation Models for Long-Form Music Generation
Ruibin Yuan, Hanfeng Lin, Shuyue Guo +55
We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the…
Are you really listening? Boosting Perceptual Awareness in Music-QA Benchmarks
Yongyi Zang, Sean O'Brien, Taylor Berg-Kirkpatrick +2
Large Audio Language Models (LALMs), where pretrained text LLMs are finetuned with audio input, have made remarkable progress in music understanding. However, current evaluation me…
Music Source Restoration
Yongyi Zang, Zheqi Dai, Mark D. Plumbley +1
We introduce Music Source Restoration (MSR), a novel task addressing the gap between idealized source separation and real-world music production. Current Music Source Separation (M…