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…
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…
Training-Free Multi-Step Audio Source Separation
Yongyi Zang, Jingyi Li, Qiuqiang Kong
Audio source separation aims to separate a mixture into target sources. Previous audio source separation systems usually conduct one-step inference, which does not fully explore th…
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…