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Annual Review of Linguistics

Volume 11, 2025

Computational Architecture of Speech Comprehension in the Human Brain

Abstract

Understanding the computational algorithm that gives rise to human language is a shared endeavor among neuroscience, linguistics, and machine learning. We propose a conceptual framework for making measurable progress toward this goal by studying the subcomponents of the processing system: its underlying representations, operations, and information flow. We review evidence from neurophysiology, neuropsychology, linguistic theory, and computational modeling and suggest future directions to push the field forward in developing a precise characterization of spoken language understanding. Overall, we claim that representations of speech properties, and the operations that generate and manipulate those representations, exist within a highly parallel, highly redundant spatiotemporal regime.

Keyword(s): comprehension, computation, language, machine learning, processing, speech
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2025-02-03
2025-06-15
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Computational Architecture of Speech Comprehension in the Human Brain
Annual Review of Linguistics 11, 209 (2025); https://doi.org/10.1146/annurev-linguistics-031120-111245
/content/journals/10.1146/annurev-linguistics-031120-111245
/content/journals/10.1146/annurev-linguistics-031120-111245
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