Publication
Title
Associative neural networks for machine consciousness: improving existing ai technologies
Author
Abstract
In this research we look at ways for improving existing AI techniques by the use of associative neural networks, proposed by Haikonen for machine consciousness. We find that all examined technologies do profit from such an approach: speech recognition, emotion recognition in speech, EMG data analysis for multilingual speech processing, the simulation of bistable perception and the generation of random numbers. EMG data analysis for multilingual speech processing (silent speech recognition) is selected as the main example in this paper for its simple yet complete architecture. We discuss the development of a test bench and give an overview of results obtained.
Language
English
Source (journal)
2008 IEEE 25TH CONVENTION OF ELECTRICAL AND ELECTRONICS ENGINEERS IN
ISRAEL, VOLS 1 AND 2
Source (book)
AIAA 47th Aerospace Sciences Meeting and Exhibit, JAN 05-08, 2009, Orlando, FL
Publication
New york : Ieee, 2008
ISBN
978-1-4244-2481-8
Volume/pages
p. 11-15
ISI
000265073200003
Full text (Publisher's DOI)
UAntwerpen
Publication type
Subject
External links
Web of Science
Record
Identification
Creation 01.03.2012
Last edited 22.10.2017