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. 2023 Apr 20;13:6480. doi: 10.1038/s41598-023-33384-9

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© The Author(s) 2023

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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(a) Values of the first convolutional layer (Conv1) when the stimulus used in the brain experiment is the input to the Discriminator network. The figure shows averaged values across two replications of each model (DIMEx-trained or Spanish and TIMIT-trained or English). Values of the TIMIT outputs were increased by + 0.0025 on the y-axis to facilitate the comparison between signals. (b) Averaged values of the first convolutional layer (Conv1) when the stimulus used in the brain experiment is the input to the Discriminator network, zoomed in to the first period. Values of the TIMIT outputs were increased by + 0.0025 on the y-axis to facilitate the comparison between signals. (c) Individual values for each model (TIMIT1, TIMIT2, DIMEx1, DIMEx2) of the first convolutional layer (Conv1) when the stimulus used in the brain experiment is the input to the Discriminator network. (d) Individual values for each model (TIMIT1, TIMIT2, DIMEx1, DIMEx2) of the first convolutional layer (Conv1) when the stimulus used in the brain experiment is the input to the Discriminator network, zoomed in to the first period.