A Comparison of Low-Complexity Real-Time Feature Extraction for Neuromorphic Speech Recognition

This paper presents a real-time, low-complexity neuromorphic speech recognition system using a spiking silicon cochlea, a feature extraction module and a population encoding method based Neural Engineering Framework (NEF)/Extreme Learning Machine (ELM) classifier IC. Several feature extraction metho...

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Detalles Bibliográficos
Autores principales: Acharya, Jyotibdha, Patil, Aakash, Li, Xiaoya, Chen, Yi, Liu, Shih-Chii, Basu, Arindam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882819/
https://www.ncbi.nlm.nih.gov/pubmed/29643760
http://dx.doi.org/10.3389/fnins.2018.00160

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882819/
https://www.ncbi.nlm.nih.gov/pubmed/29643760
http://dx.doi.org/10.3389/fnins.2018.00160

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