Natural language processing (NLP) in Artificial Intelligence (AI): a functional linguistic perspective

Panesar, Kulvinder (2018) Natural language processing (NLP) in Artificial Intelligence (AI): a functional linguistic perspective. In: Artificial Intelligence and Information: A Multidisciplinary Perspective. Vernon Press (In Press)

Text (Book chapter proposal) NLP in AI Abstract BkChpter KulvinderPanesar 14-6-18.pdf - Accepted Version Restricted to Repository staff only Download (157kB) Request a copy

Abstract

This chapter encapsulates the multi-disciplinary nature that facilitates NLP in AI. It identifies work of a linguistically orientated conversational software agent (CSA) (Panesar, 2017) framework sensitive to natural language processing (NLP) concepts, language and the agent environment. A long-standing issue within NLP CSA systems is refining the accuracy of interpretation to provide realistic dialogue to support the human-to-computer communication. Motivated by this, we present novel computational approach of using Role and Reference Grammar (RRG) – a strong, mature, functional linguistic theory as the linguistic engine of a perceiving utterances (via speech act performatives), for further integration, cognitive manipulation and planning to create a grammatical correct RRG based response.

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