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

• Main Authors: Acharya, Jyotibdha, Patil, Aakash, Li, Xiaoya, Chen, Yi, Liu, Shih-Chii, Basu, Arindam
• Other Authors: Interdisciplinary Graduate School (IGS)
• Format: 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
• Institution: Nanyang Technological University

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...