Appropriate Microplanning Choices for Low-Skilled Readers

We have developed a set of microplanning choice rules which are intended to enable Natural Language Generation (NLG) systems to generate appropriate texts for readers with below-average literacy, focusing in particular on choices related to how discourse structure is expressed (cue phrases, ordering, sentence structure). Evaluation experiments suggest that our rules do enhance the readability of texts for low-skilled readers, although there is still room for improvement

A Flexible pragmatics-driven language generator for animated agents

This paper describes the NECA MNLG; a fully implemented Multimodal Natural Language Generation module. The MNLG is deployed as part of the NECA system which generates dialogues between animated agents. The generation module supports the seamless integration of full grammar rules, templates and canned text. The generator takes input which allows for the specification of syntactic, semantic and pragmatic constraints on the output

Capturing mink and data : Interacting with a small and dispersed environmental initiative over the introduction of digital innovation

This case study was carried out by Koen Arts1, Gemma Webster1, Nirwan Sharma1, Yolanda Melero2, Chris Mellish1, Xavier Lambin2 and René van der Wal1. We thank two anonymous reviewers for their suggestions, and Chris Horrill from SMI for his very helpful and insightful comments on previous drafts of this manuscript. The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.Case study for 'Responsible Research & Innovation in ICT' platformPostprin

Generating High-Quality Surface Realizations Using Data Augmentation and Factored Sequence Models

This work presents a new state of the art in reconstruction of surface realizations from obfuscated text. We identify the lack of sufficient training data as the major obstacle to training high-performing models, and solve this issue by generating large amounts of synthetic training data. We also propose preprocessing techniques which make the structure contained in the input features more accessible to sequence models. Our models were ranked first on all evaluation metrics in the English portion of the 2018 Surface Realization shared task

Generating natural language descriptions of Z test cases

Critical software most often requires an independent validation and verification (IVV). IVV is usually performed by domain experts, who are not familiar with specific, many times formal, development technologies. In addition, model-based testing (MBT) is a promising testing technique for the verification of critical software. Test cases generated by MBT tools are logical descriptions. The problem is, then, to provide natural language (NL) descriptions of these test cases, making them accessible to domain experts. In this paper, we present ongoing research aimed at finding a suitable method for generating NL descriptions from test cases in a formal specification language. A first prototype has been developed and applied to a real-world project in the aerospace sector

Generating ellipsis using discourse structures

This article describes an effort to generate elliptic sentences, using Dependency Trees connected by Discourse Relations as input. We contend that the process of syntactic aggregation should be performed in the Surface Realization stage of the language generation process, and that Dependency Trees with Rhetorical Relations are excellent input for a generation system that has to generate ellipsis. We also propose a taxonomy of the most common Dutch cue words, grouped according to the kind of discourse relations they signal

The psychology of gestures and gesture-like movements in non-human primates

Research into gestural communication of nonhuman primates is often inspired by an interest in the evolutionary roots of human language. The focus on intentionally used behaviors is central to this approach that aims at investigating the cognitive mechanisms characterizing gesture use in monkeys and apes. This chapter describes some of the key characteristics that are important in this context, and discusses the evidence the claim is built on that gestures of, nonhuman primates represent intentionally and flexibly used means of communication. This chapter will first provide a brief introduction into what primates are and how a gesture is defined, before the psychological approach to gestural communication is described in more detail, with focus on the cognitive mechanisms underlying gesture use in nonhuman primates