Teaching natural language to computers

TL;DR

This paper explores how computers can understand and generate natural language by examining the underlying structures and processes involved, emphasizing the importance of context, self-awareness, and embodiment in language applications.

Contribution

It introduces a framework for analyzing language-like applications in computers, focusing on the modalities and modules involved in natural language processing.

Findings

Identifies key modules involved in language processing

Highlights the importance of context and embodiment

Proposes questions to improve language understanding in AI

Abstract

"Natural Language," whether spoken and attended to by humans, or processed and generated by computers, requires networked structures that reflect creative processes in semantic, syntactic, phonetic, linguistic, social, emotional, and cultural modules. Being able to produce novel and useful behavior following repeated practice gets to the root of both artificial intelligence and human language. This paper investigates the modalities involved in language-like applications that computers -- and programmers -- engage with, and aims to fine tune the questions we ask to better account for context, self-awareness, and embodiment.