Recurrent neural networks as neuro-computational models of human speech recognition.
Human speech recognition transforms a continuous acoustic signal into categorical linguistic units, by aggregating information that is distributed in time. It has been suggested that this kind of information processing may be understood through the computations of a Recurrent Neural Network (RNN) th...
Saved in:
| Main Authors: | Christian Brodbeck, Thomas Hannagan, James S Magnuson |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-07-01
|
| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1013244 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Advancing human activity recognition with quaternion-based recurrent neural networks
by: S. Gayathri Devi, et al.
Published: (2025-07-01) -
Perception of Phonological Assimilation by Neural Speech Recognition Models
by: Charlotte Pouw, et al.
Published: (2024-09-01) -
Optimizing Speech Emotion Recognition with Hilbert Curve and convolutional neural network
by: Zijun Yang, et al.
Published: (2024-01-01) -
Analysis of the sports action recognition model based on the LSTM recurrent neural network
by: Chen Ping, et al.
Published: (2025-02-01) -
Convolutional neural network for gesture recognition human-computer interaction system design.
by: Peixin Niu
Published: (2025-01-01)