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 …

One of the hardest problems in the area of Natural Language Processing and Artificial
Intelligence is automatically generating language that is coherent and understandable to …

We report a study of referential choice in discourse production, understood as the choice
between various types of referential devices, such as pronouns and full noun phrases. Our …

We present Alto, a rapid prototyping tool for new grammar formalisms. Alto implements
generic but efficient algorithms for parsing, translation, and training for a range of …

The referring expressions (REs) produced by a natural language generation (NLG) system
can be misunderstood by the hearer, even when they are semantically correct. In an …

While most current frameworks for reference handling are based on binary truth-theoretic
knowledge representation, in this thesis I argue for a perspective on reference which …

When generating technical instructions, it is often necessary to describe an object that does
not exist yet. For example, an NLG system which explains how to build a house needs to …

We present a model which predicts how individual users of a dialog system understand and
produce utterances based on user groups. In contrast to previous work, these user groups …

Natural Language Generation (NLG) is the research subfield which lies in the intersection
between artificial intelligence and computational linguistic and has the goal to create …

Integrating surface realization and the generation of referring expressions into a single
algorithm can improve the quality of the generated sentences. Existing algorithms for doing …