Semantic Scholar Open Access 2024 2 sitasi

Computational Architecture of Speech Comprehension in the Human Brain

Laura Gwilliams Ilina Bhaya-Grossman Yizhen Zhang Terri L. Scott Sarah Harper +1 lainnya

Abstrak

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.

Penulis (6)

L

Laura Gwilliams

I

Ilina Bhaya-Grossman

Y

Yizhen Zhang

T

Terri L. Scott

S

Sarah Harper

D

D. Levy

Format Sitasi

Gwilliams, L., Bhaya-Grossman, I., Zhang, Y., Scott, T.L., Harper, S., Levy, D. (2024). Computational Architecture of Speech Comprehension in the Human Brain. https://doi.org/10.1146/annurev-linguistics-031120-111245

Akses Cepat

Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.1146/annurev-linguistics-031120-111245
Akses
Open Access ✓