University of Hull logo

Transparency of execution using epigenetic networks (2017)
Conference Proceeding
Dethlefs, N., & Turner, A. (2017). Transparency of execution using epigenetic networks. In C. Knibbe, G. Beslon, D. Parsons, D. Misevic, J. Rouzaud-Cornabas, N. Bredeche, …H. Soula (Eds.), Proceedings of the ECAL 2017, 404-411. doi:10.7551/ecal_a_068

This paper describes how the recurrent connectionist architecture epiNet, which is capable of dynamically modifying its topology, is able to provide a form of transparent execution. EpiNet, which is inspired by eukaryotic gene regulation in nature, i... Read More

Domain transfer for deep natural language generation from abstract meaning representations (2017)
Journal Article
Dethlefs, N. (2017). Domain transfer for deep natural language generation from abstract meaning representations. IEEE computational intelligence magazine, 12(3), 18-28. doi:10.1109/mci.2017.2708558

Stochastic natural language generation systems that are trained from labelled datasets are often domainspecific in their annotation and in their mapping from semantic input representations to lexical-syntactic outputs. As a result, learnt models fail... Read More

Information density and overlap in spoken dialogue (2015)
Journal Article
Cuayahuitl, H., Dethlefs, N., Cuayáhuitl, H., Hastie, H., Lemon, O., Rieser, V., & Yu, Y. (2016). Information density and overlap in spoken dialogue. Computer speech & language, 37, (82-97). doi:10.1016/j.csl.2015.11.001. ISSN 0885-2308

Incremental dialogue systems are often perceived as more responsive and natural because they are able to address phenomena of turn-taking and overlapping speech, such as backchannels or barge-ins. Previous work in this area has often identified disti... Read More

Hierarchical reinforcement learning for situated natural language generation (2014)
Journal Article
Dethlefs, N., & Cuayáhuitl, H. (2015). Hierarchical reinforcement learning for situated natural language generation. Natural language engineering, 21(3), 391-435. doi:10.1017/S1351324913000375

Natural Language Generation systems in interactive settings often face a multitude of choices, given that the communicative effect of each utterance they generate depends crucially on the interplay between its physical circumstances, addressee and in... Read More