Predicting the limits of variability in discourse using neural models
PI(s): Prof. Dr. David Schlangen & Prof. Dr. Manfred Stede
We investigate the notion of utterance acceptability in context, and through it, the underlying competence notion coherence, understanding it quite directly as a limit on variability in discourse follow-ups. We will assemble a test suite of relevant cases (in English), and collect acceptability judgements. Building on this, we will study which aspects of this notion, if any, neural language models capture. Finally, we will use the results of these studies to investigate whether we can improve the models by providing inductive biases that introduce discourse structural knowledge. A particular focus in these studies is on coherence in dialogue.
Sixth Summer School on Statistical Methods for Linguistics and Psychology
One goal of the summer school is to provide comprehensive training in the theory and application of statistics, with a…
Workshop: Basics of Artificial Neural Networks / Deep Learning
The SFB1287 at the University Potsdam invites interested researchers of linguistics to a free this workshop.This 2-day workshop offers an…