A comparison of low-complexity real-time feature extraction for neuromorphic speech recognition

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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Bibliographic Details
Main Authors: Acharya, Jyotibdha, Patil, Aakash, Li, Xiaoya, Chen, Yi, Liu, Shih-Chii, Basu, Arindam
Other Authors: Interdisciplinary Graduate School (IGS)
Format: Journal Article
Language:English
Published: 2018
Subjects:
Silicon Cochlea
Neural Engineering Framework
Online Access:https://hdl.handle.net/10356/85120
http://hdl.handle.net/10220/45134

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