A System for Automatic English Text Expansion
Silvia Garc\'ia M\'endez, Milagros Fern\'andez Gavilanes, Enrique, Costa Montenegro, Jonathan Juncal Mart\'inez, Francisco Javier Gonz\'alez, Casta\~no, Ehud Reiter

TL;DR
This paper introduces an adaptable, rule-based and statistical English text expansion system capable of generating coherent sentences from minimal input, with applications in AAC and potential for other domains.
Contribution
It presents a modular, language-agnostic NLG system with a comprehensive lexicon and demonstrates its effectiveness through evaluations in English and Spanish.
Findings
High accuracy in regenerating corpus sentences
Effective text expansion demonstrated in AAC applications
Comparable quality of English and Spanish text expansion
Abstract
We present an automatic text expansion system to generate English sentences, which performs automatic Natural Language Generation (NLG) by combining linguistic rules with statistical approaches. Here, "automatic" means that the system can generate coherent and correct sentences from a minimum set of words. From its inception, the design is modular and adaptable to other languages. This adaptability is one of its greatest advantages. For English, we have created the highly precise aLexiE lexicon with wide coverage, which represents a contribution on its own. We have evaluated the resulting NLG library in an Augmentative and Alternative Communication (AAC) proof of concept, both directly (by regenerating corpus sentences) and manually (from annotations) using a popular corpus in the NLG field. We performed a second analysis by comparing the quality of text expansion in English to Spanish,…
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Taxonomy
MethodsSparse Evolutionary Training · Lib
