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Parallel hierarchical encoding of linguistic representations in the human auditory cortex and recurrent automatic speech recognition systems | Synapse
March 3, 2026
Parallel hierarchical encoding of linguistic representations in the human auditory cortex and recurrent automatic speech recognition systems
MK
Menoua Keshishian
Columbia University
GM
Gavin Mischler
Columbia University
ST
Samuel Thomas
IBM (United States)
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Puntos clave
Linguistic representations are encoded hierarchically in the auditory cortex and AI systems, indicating a deep connection.
The study shows that both human auditory processing and advanced speech recognition systems use similar neural patterns.
Analysis compares auditory cortex activity with recurrent machine learning systems designed for speech recognition.
These findings highlight the potential for improved AI speech systems based on human language processing principles.
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Keshishian et al. (Tue,) studied this question.
synapsesocial.com/papers/69a761e0c6e9836116a2ff4e
https://doi.org/https://doi.org/10.1038/s42256-026-01185-0