Associative neural networks for machine consciousness: Improving existing AI technologies

• Published in: 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel pp. 011 - 015
• Main Authors: Lesser, E., Schaeps, T., Haikonen, P., Jorgensen, C.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2008
• Subjects: Analytical models; Artificial intelligence; Data analysis; Electromyography; Emotion recognition; Neural networks; Random number generation; Speech analysis; Speech processing; Speech recognition
• DOI: 10.1109/EEEI.2008.4736701
• ISBN: 142442481X; 9781424424818

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.