Incremental learning and forgetting in incremental stochastic turn-taking models
2011 (English)In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, Florence, Italy, 2011, 2080-2083 p.Conference paper (Refereed)
We present a computational framework for stochastically modeling dyad interaction chronograms. The framework's most novel feature is the capacity for incremental learning and forgetting. To showcase its flexibility, we design experiments answering four concrete questions about the systematics of spoken interaction. The results show that: (1) individuals are clearly affected by one another; (2) there is individual variation in interaction strategy; (3) strategies wander in time rather than converge; and (4) individuals exhibit similarity with their interlocutors. We expect the proposed framework to be capable of answering many such questions with little additional effort.
Place, publisher, year, edition, pages
Florence, Italy, 2011. 2080-2083 p.
Computer Science Language Technology (Computational Linguistics)
IdentifiersURN: urn:nbn:se:kth:diva-52203ISI: 000316502201009ScopusID: 2-s2.0-84865790016ISBN: 978-1-61839-270-1OAI: oai:DiVA.org:kth-52203DiVA: diva2:465501
12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011; Florence; Italy; 27 August 2011 through 31 August 2011
tmh_import_11_12_14 QC 201201032011-12-142011-12-142014-01-15Bibliographically approved