Discourse structure and information structure : interfaces and prosodic realization

In this paper we review the current state of research on the issue of discourse structure (DS) / information structure (IS) interface. This field has received a lot of attention from discourse semanticists and pragmatists, and has made substantial progress in recent years. In this paper we summarize the relevant studies. In addition, we look at the issue of DS/ISinteraction at a different level—that of phonetics. It is known that both information structure and discourse structure can be realized prosodically, but the issue of phonetic interaction between the prosodic devices they employ has hardly ever been discussed in this context. We think that a proper consideration of this aspect of DS/IS-interaction would enrich our understanding of the phenomenon, and hence we formulate some related research-programmatic positions

On General Language Understanding

Natural Language Processing prides itself to be an empirically-minded, if not outright empiricist field, and yet lately it seems to get itself into essentialist debates on issues of meaning and measurement ("Do Large Language Models Understand Language, And If So, How Much?"). This is not by accident: Here, as everywhere, the evidence underspecifies the understanding. As a remedy, this paper sketches the outlines of a model of understanding, which can ground questions of the adequacy of current methods of measurement of model quality. The paper makes three claims: A) That different language use situation types have different characteristics, B) That language understanding is a multifaceted phenomenon, bringing together individualistic and social processes, and C) That the choice of Understanding Indicator marks the limits of benchmarking, and the beginnings of considerations of the ethics of NLP use.Comment: Findings of EMNLP 202

Towards Finding and Fixing Fragments–-Using ML to Identify Non-Sentential Utterances and their Antecedents in Multi-Party Dialogue

Schlangen D. Towards Finding and Fixing Fragments–-Using ML to Identify Non-Sentential Utterances and their Antecedents in Multi-Party Dialogue. In: Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL05). Ann Arbor, Michigan: Association for Computational Linguistics; 2005: 247-254

Modelling dialogue: Challenges and Approaches

Schlangen D. Modelling dialogue: Challenges and Approaches. Künstliche Intelligenz. 2005;3/05:23-28

Causes and Strategies for Requesting Clarification in Dialogue

Schlangen D. Causes and Strategies for Requesting Clarification in Dialogue. In: Proceedings of the 5th Workshop of the ACL SIG on Discourse and Dialogue. Boston, USA; 2004

The Potsdam Dialogue Corpora: Experiment Handbook

Schlangen D, Fernández R. The Potsdam Dialogue Corpora: Experiment Handbook. Potsdam, Germany: University of Potsdam; 2008