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

• المؤلفون الرئيسيون: Acharya, Jyotibdha, Patil, Aakash, Li, Xiaoya, Chen, Yi, Liu, Shih-Chii, Basu, Arindam
• مؤلفون آخرون: Interdisciplinary Graduate School (IGS)
• التنسيق: مقال
• اللغة: English
• منشور في: 2018
• الموضوعات: Silicon Cochlea; Neural Engineering Framework
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/85120; http://hdl.handle.net/10220/45134
• المؤسسة: 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...