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. 2023 Oct 30;26(12):2213–2225. doi: 10.1038/s41593-023-01468-4

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© The Author(s). 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 2 — Example of feature extraction for a sample sentence, read by a male speaker:’It is well liked by the children and faculty.’ From top to bottom: 1) raw waveform; 2) high-gamma (z-scored) activity at an example electrode; 3) Mel-scaled spectrogram; 4) intensity of voicing; 5) sentence onset; 6) time course of peak rate; 7) absolute pitch (binned into 10 bins); 8) relative pitch (binned into 10 bins); 9) pitch change (binned into 10 bins); 10) phonetic features.