Computational Cognitive Activation Function Using fMRI Application

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Kanna, R. Kishore and Singh, Priyanka and Ghosh, Ankush and Shaw, Rabindra Nath and Suvetha, G (2026) Computational Cognitive Activation Function Using fMRI Application. In: Advanced Computing and Intelligent Technologies, Lecture Notes in Networks and Systems. Springer Nature Singapore, pp. 915-929.

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Official URL: https://doi.org/10.1007/978-981-96-4933-4_59

Abstract

The literature suggests that speech representations derived from pretrained self-supervised systems show similarities to human speech perceptual brain
mechanisms, and that subsequent challenges may increase the similarity again by
fine-tuning speech positions. Therefore, in this study, we propose to match the model
representation with human neural responses using fMRI brain activation to improve
the widely applicable wav2vec2.0 model. According to the SUPERB testing analysis,
this processing is useful for many underlying tasks such as attention segmentation,
automatic voice recognition, and speaker verification. The result is conditioned path
recognition the intelligence as an alternative to enhancing self-supervised speech
processing.

Item Type:	Book Section
Subjects:	Electronics and Communication Engineering > Network Theory Electronics and Communication Engineering > Data Communication
Domains:	Electronics and Communication Engineering
Depositing User:	Mr Sureshkumar A
Date Deposited:	16 Dec 2025 06:37
Last Modified:	16 Dec 2025 06:37
URI:	https://ir.vistas.ac.in/id/eprint/11506

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