Associative neural networks for machine consciousness: Improving existing AI technologies

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.