Natural Language Generation Using Link Grammar for General Conversational Intelligence

TL;DR

This paper introduces a novel natural language generation method using Link Grammar, significantly improving grammatical sentence generation for conversational AI and potentially serving as a key component in proto-AGI systems.

Contribution

The paper presents a new automatic sentence generation technique leveraging Link Grammar, outperforming existing methods and enhancing natural language understanding in AI systems.

Findings

Outperforms current state-of-the-art baselines in grammatical sentence generation

Enables more natural and human-like language output in AI systems

Potentially serves as a core component in proto-AGI question answering pipelines

Abstract

Many current artificial general intelligence (AGI) and natural language processing (NLP) architectures do not possess general conversational intelligence--that is, they either do not deal with language or are unable to convey knowledge in a form similar to the human language without manual, labor-intensive methods such as template-based customization. In this paper, we propose a new technique to automatically generate grammatically valid sentences using the Link Grammar database. This natural language generation method far outperforms current state-of-the-art baselines and may serve as the final component in a proto-AGI question answering pipeline that understandably handles natural language material.