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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Acharya, Jyotibdha, Patil, Aakash, Li, Xiaoya, Chen, Yi, Liu, Shih-Chii, Basu, Arindam
Άλλοι συγγραφείς: Interdisciplinary Graduate School (IGS)
Μορφή: Journal Article
Γλώσσα:English
Έκδοση: 2018
Θέματα:
Silicon Cochlea
Neural Engineering Framework
Διαθέσιμο Online:https://hdl.handle.net/10356/85120
http://hdl.handle.net/10220/45134

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