The same speech content produced by different speakers exhibits significant differences in pitch contour, yet listeners' semantic perception remains unaffected. This phenomenon may stem from the brain's perception of pitch contours being independent of individual speakers' pitch ranges. In this work, we recorded electroencephalogram (EEG) while participants listened to Mandarin monosyllables with varying tones, phonemes, and speakers. The CE-ViViT model is proposed to decode raw or speaker-normalized pitch contours directly from EEG. Experimental results demonstrate that the proposed model can decode pitch contours with modest errors, achieving performance comparable to state-of-the-art EEG regression methods. Moreover, speaker-normalized pitch contours were decoded more accurately, supporting the neural encoding of relative pitch.
@article{arxiv.2505.19626,
title = {Decoding Speaker-Normalized Pitch from EEG for Mandarin Perception},
author = {Jiaxin Chen and Yiming Wang and Ziyu Zhang and Jiayang Han and Yin-Long Liu and Rui Feng and Xiuyuan Liang and Zhen-Hua Ling and Jiahong Yuan},
journal= {arXiv preprint arXiv:2505.19626},
year = {2025}
}