Human-machine cognitive coalescence through an internal duplex interface

Abstract

In this thesis, we present a non-invasive and non-intrusive system that enables silent duplex human-machine communication and enables an interface that is internal to the user. We present a peripheral nerve-computer interface, AlterEgo, that allows a user to silently converse with a computing device without any voice or any discernible movements - thereby enabling the user to communicate with devices, AI assistants, applications or other people in a silent, concealed and seamless manner. A user's volitional internally articulated speech is characterized by efferent signal signatures in internal speech articulators that are captured and recognized by the proposed system. The hope is to facilitate a natural language user interface, where users can silently communicate in natural language and receive information and sensory input aurally through bone conduction. This enables a discreet, closed-loop interface with a computing device, and thus providing a seamless form of cognitive augmentation. The goal of the thesis is to describe the architecture, design, implementation and operation of the entire system along with demonstrating the utility of the platform as a personal computing system.