Neural signals, machine learning, and the future of inner speech recognition

Neural signals, machine learning, and the future of inner speech recognition

Inner speech recognition (ISR) is an emerging field with significant potential for applications in brain-computer interfaces (BCIs) and assistive technologies. This review focuses on the critical role of machine learning (ML) in decoding inner speech, exploring how various ML techniques improve the...

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Bibliographic Details
Main Authors: Adiba Tabassum Chowdhury, Ahmed Hassanein, Aous N. Al Shibli, Youssuf Khanafer, Mohannad Natheef AbuHaweeleh, Shona Pedersen, Muhammad E. H. Chowdhury
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Human Neuroscience
Subjects:
inner speech recognition
inner overt speech
machine learning
deep learning
speech decoding
waves to words
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2025.1637174/full
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https://www.frontiersin.org/articles/10.3389/fnhum.2025.1637174/full

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