enunlg: a Python library for reproducible neural data-to-text experimentation
Conference Proceeding
Howcroft, D. M., & Gkatzia, D. (2023)
enunlg: a Python library for reproducible neural data-to-text experimentation. In Proceedings of the 16th International Natural Language Generation Conference: System Demonstrations (4-5
Over the past decade, a variety of neural ar-chitectures for data-to-text generation (NLG) have been proposed. However, each system typically has its own approach to pre-and p...
Building a dual dataset of text-and image-grounded conversations and summarisation in Gàidhlig (Scottish Gaelic)
Conference Proceeding
Howcroft, D. M., Lamb, W., Groundwater, A., & Gkatzia, D. (2023)
Building a dual dataset of text-and image-grounded conversations and summarisation in Gàidhlig (Scottish Gaelic). In Proceedings of the 16th International Natural Language Generation Conference (443-448
Gàidhlig (Scottish Gaelic; gd) is spoken by about 57k people in Scotland, but remains an under-resourced language with respect to natural language processing in general and na...
LOWRECORP: the Low-Resource NLG Corpus Building Challenge
Conference Proceeding
Chandu, K. R., Howcroft, D., Gkatzia, D., Chung, Y., Hou, Y., Emezue, C., …Adewumi, T. (2023)
LOWRECORP: the Low-Resource NLG Corpus Building Challenge. In The 16th International Natural Language Generation Conference: Generation Challenges (1-9
Most languages in the world do not have sufficient data available to develop neural-network-based natural language generation (NLG) systems. To alleviate this resource scarcit...
What happens if you treat ordinal ratings as interval data? Human evaluations in {NLP} are even more under-powered than you think
Conference Proceeding
Howcroft, D. M., & Rieser, V. (2021)
What happens if you treat ordinal ratings as interval data? Human evaluations in {NLP} are even more under-powered than you think. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (8932-8939
Previous work has shown that human evaluations in NLP are notoriously under-powered. Here, we argue that there are two common factors which make this problem even worse: NLP s...
OTTers: One-turn Topic Transitions for Open-Domain Dialogue
Conference Proceeding
Sevegnani, K., Howcroft, D. M., Konstas, I., & Rieser, V. (2021)
OTTers: One-turn Topic Transitions for Open-Domain Dialogue. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) (2492-2504). https://doi.org/10.18653/v1/2021.acl-long.194
Mixed initiative in open-domain dialogue requires a system to pro-actively introduce new topics. The one-turn topic transition task explores how a system connects two topics i...
How speakers adapt object descriptions to listeners under load
Journal Article
Vogels, J., Howcroft, D. M., Tourtouri, E., & Demberg, V. (2020)
How speakers adapt object descriptions to listeners under load. Language, Cognition and Neuroscience, 35(1), 78-92. https://doi.org/10.1080/23273798.2019.1648839
A controversial issue in psycholinguistics is the degree to which speakers employ audience design during language production. Hypothesising that a consideration of the listene...
G-TUNA: a corpus of referring expressions in German, including duration information
Conference Proceeding
Howcroft, D., Vogels, J., & Demberg, V. (2017)
G-TUNA: a corpus of referring expressions in German, including duration information. In Proceedings of the 10th International Conference on Natural Language Generation (149-153). https://doi.org/10.18653/v1/w17-3522
Corpora of referring expressions elicited from human participants in a controlled environment are an important resource for research on automatic referring expression generati...
Inducing Clause-Combining Rules: A Case Study with the SPaRKy Restaurant Corpus
Conference Proceeding
White, M., & Howcroft, D. M. (2015)
Inducing Clause-Combining Rules: A Case Study with the SPaRKy Restaurant Corpus. In Proceedings of the 15th European Workshop on Natural Language Generation (ENLG) (28-37). https://doi.org/10.18653/v1/w15-4704
We describe an algorithm for inducing clause-combining rules for use in a traditional natural language generation architecture. An experiment pairing lexicalized text plans fr...