Self-supervised models of audio effectively explain human cortical responses to speech

27 May 2022

Papers citing "Self-supervised models of audio effectively explain human cortical responses to speech"

9 / 9 papers shown

Title
BrainWavLM: Fine-tuning Speech Representations with Brain Responses to Language Nishitha Vattikonda A. Vaidya Richard Antonello Alexander G. Huth 106 0 0 13 Feb 2025
Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey) S. Oota Zijiao Chen Manish Gupta R. Bapi G. Jobard F. Alexandre X. Hinaut 3DV AI4CE 49 11 0 31 Dec 2024
Improving Semantic Understanding in Speech Language Models via Brain-tuning Omer Moussa Dietrich Klakow Mariya Toneva 49 3 0 11 Oct 2024
Refining Self-Supervised Learnt Speech Representation using Brain Activations Hengyu Li Kangdi Mei Zhaoci Liu Yang Ai Liping Chen Jie Zhang Zhenhua Ling SSL 26 1 0 12 Jun 2024
Mapping Brains with Language Models: A Survey Antonia Karamolegkou Mostafa Abdou Anders Søgaard 16 9 0 08 Jun 2023
Scaling laws for language encoding models in fMRI Richard Antonello Aditya R. Vaidya Alexander G. Huth MedIm 30 55 0 19 May 2023
Improved Decoding of Attentional Selection in Multi-Talker Environments with Self-Supervised Learned Speech Representation Cong Han Vishal B. Choudhari Yinghao Aaron Li N. Mesgarani 16 3 0 11 Feb 2023
Decoding speech perception from non-invasive brain recordings Alexandre Défossez Charlotte Caucheteux Jérémy Rapin Ori Kabeli J. King 35 116 0 25 Aug 2022
Inductive biases, pretraining and fine-tuning jointly account for brain responses to speech Juliette Millet J. King 53 34 0 25 Feb 2021