arXiv:2606. 16612v1 Announce Type: cross Abstract: The rapid advancement of AI music generators highlights the urgent need for reliable Synthetic Song Detection (SSD).
By Yan Han, Zhibin Wen, Yuan Wang, Shuangrun Shao, Xiaobing Li, Yang Xu, Wei Li
arXiv:2608. 07285v1 Announce Type: cross Abstract: AI-generated music is increasingly used at the stem level, with producers integrating synthetic drums, basslines, or vocals alongside human-performed instruments.
By Fernando Garcia de la Cruz, David L\'opez-Ayala, Pablo Zinemanas, Emilio Molina, Mart\'in Rocamora
arXiv:2603. 23667v2 Announce Type: replace-cross Abstract: We introduce Echoes, a new dataset for music deepfake detection designed for training and benchmarking detectors under realistic and provider-diverse conditions.
By Octavian Pascu, Dan Oneata, Horia Cucu, Nicolas M. Muller
arXiv:2609.31810v2 Announce Type: replace-cross
Abstract: Video-to-music models have advanced considerably in the last few years, particularly in film and music video applications. In this paper, we...
By Felipe Marra, Lucas N. Ferreira
arXiv:2606. 01686v1 Announce Type: cross Abstract: As generative platforms such as Suno and Udio reach human-grade audio quality, the scope of AI's utility has expanded across the entire music production workflow.
By Seonghyeon Go, Yumin Kim
arXiv:2608. 04142v1 Announce Type: cross Abstract: Existing reference-free methods for evaluating music perceptual quality alleviate the need for paired noisy-clean data, but they still rely on a background set, which is used to compute aggregated statistics of clean audio samples.
By Alon Ziv, Harel Pogoda, Yossi Adi