This paper surveys the current state of the art in Natural Language Generation (NLG),
defined as the task of generating text or speech from non-linguistic input. A survey of NLG is …

Abstract Natural Language Generation (NLG) is defined as the systematic approach for
producing human understandable natural language text based on non-textual data or from …

This article offers a survey of computational research on referring expression generation
(REG). It introduces the REG problem and describes early work in this area, discussing what …

Data-to-text systems are Natural Language Generation (NLG) systems which generate texts
from noninguistic inpūt data, such as sensordātā ānd event logs. Such systems need to …

This research aims to contribute to the unexplored field of audience studies with a focus on
the credibility of automated journalism. In this paper, we take a systematic look into the …

Two important recent trends in natural language generation are (i) probabilistic techniques
and (ii) comprehensive approaches that move away from traditional strictly modular and …

Abstract Contemporary Neonatal Intensive Care Units collect vast amounts of patient data in
various formats, making efficient processing of information by medical professionals difficult …

We present NaturalOWL, a natural language generation system that produces texts
describing individuals or classes of OWL ontologies. Unlike simpler OWL verbalizers, which …

An argument that computational models can shed light on referring, a fundamental and
much-studied aspect of communication. To communicate, speakers need to make it clear …

Speakers often overspecify their target descriptions and include more information than
necessary for unique identification of the target referent. In the current paper, we study the …