Computational Architecture of Speech Comprehension in the Human Brain
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)
Laura Gwilliams
Ilina Bhaya-Grossman
Yizhen Zhang
Terri L. Scott
Sarah Harper
D. Levy
Akses Cepat
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Cek di sumber asli →- Tahun Terbit
- 2024
- Bahasa
- en
- Total Sitasi
- 2×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1146/annurev-linguistics-031120-111245
- Akses
- Open Access ✓