Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space

This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike generator. These spike trains are mapped into a f...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Kan, Príncipe, José C.
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/PMC5891646/
https://www.ncbi.nlm.nih.gov/pubmed/29666568
http://dx.doi.org/10.3389/fnins.2018.00194

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891646/
https://www.ncbi.nlm.nih.gov/pubmed/29666568
http://dx.doi.org/10.3389/fnins.2018.00194

Ejemplares similares