How Does Instrumental Music Help SingFake Detection?
ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 19072–19076 , 2026
Abstract
Although many models exist to detect singing voice deepfakes (SingFake), how these models operate, particularly with instrumental accompaniment, is unclear. We investigate how instrumental music affects SingFake detection from two perspectives. To investigate the behavioral effect, we test different backbones, unpaired instrumental tracks, and frequency subbands. To analyze the representational effect, we probe how fine-tuning alters encoders’ speech and music capabilities. Our results show that instrumental accompaniment acts mainly as data augmentation rather than providing intrinsic cues (e.g., rhythm or harmony). Furthermore, fine-tuning increases reliance on shallow speaker features while reducing sensitivity to content, paralinguistic, and semantic information. These insights clarify how models exploit vocal versus instrumental cues and can inform the design of more interpretable and robust SingFake detection systems.
BibTeX
@inproceedings{chen2025instrumental,
title = {How Does Instrumental Music Help SingFake Detection?},
author = {Chen, Xuanjun and Hu, Chia-Yu and Lin, I-Ming and Lin, Yi-Cheng and Chiu, I-Hsiang and Zhang, You and Huang, Sung-Feng and Yang, Yi-Hsuan and Wu, Haibin and Lee, Hung-yi and Jang, Jyh-Shing Roger},
booktitle = {ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2026},
pages = {19072--19076},
doi = {10.1109/ICASSP55912.2026.11460829},
}