Outputs (28)

Commonsense-enhanced Natural Language Generation for Human-Robot Interaction (2020)
Presentation / Conference Contribution
Gkatzia, D. (2020, December). Commonsense-enhanced Natural Language Generation for Human-Robot Interaction. Presented at 2nd Workshop on Natural Language Generation for Human-Robot Interaction (HRI 2020), Online

Commonsense is vital for human communication, as it allows us to make inferences without explicitly mentioning the context. Equipping robots with commonsense knowledge would lead to better communication between humans and robots and will allow robots... Read More about Commonsense-enhanced Natural Language Generation for Human-Robot Interaction.

Proceedings of the Workshop on NLG for Human–Robot Interaction (2018)
Presentation / Conference Contribution
(2018). Proceedings of the Workshop on NLG for Human–Robot Interaction. In M. Ellen Foster, H. Buschmeier, & D. Gkatzia (Eds.),

Ellen Foster, M., H. Buschmeier, & D. Gkatzia (Eds.) (2018). Proceedings of the Workshop on NLG for Human–Robot Interaction.

Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction (2018)
Presentation / Conference Contribution
Belakova, J., & Gkatzia, D. (2018). Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction. In Proceedings of the Workshop on NLG for Human–Robot Interaction (8-11)

One of the most natural ways for human robot communication is through spoken language. Training human-robot interaction systems require access to large datasets which are expensive to obtain and labour intensive. In this paper, we des... Read More about Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction.

Inflection Generation for Spanish Verbs using Supervised Learning (2017)
Presentation / Conference Contribution
Barros, C., Gkatzia, D., & Lloret, E. (2017). Inflection Generation for Spanish Verbs using Supervised Learning. In Proceedings of the First Workshop on Subword and Character Level Models in NLP (136-141). https://doi.org/10.18653/v1/W17-4120

We present a novel supervised approach to inflection generation for verbs in Spanish. Our system takes as input the verb’s lemma form and the desired features such as person, number, tense, and is able to predict the appropriate grammatical conjugati... Read More about Inflection Generation for Spanish Verbs using Supervised Learning.

Improving the Naturalness and Expressivity of Language Generation for Spanish (2017)
Presentation / Conference Contribution
Barros, C., Gkatzia, D., & Lloret, E. (2017). Improving the Naturalness and Expressivity of Language Generation for Spanish. In Proceedings of the 10th International Conference on Natural Language Generation (41-50). https://doi.org/10.18653/v1/W17-3505

We present a flexible Natural Language Generation approach for Spanish, focused on the surface realisation stage, which integrates an inflection module in order to improve the naturalness and expressivity of the generated language. This inflection mo... Read More about Improving the Naturalness and Expressivity of Language Generation for Spanish.

The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes (2016)
Presentation / Conference Contribution
Bartie, P., Mackaness, W., Gkatzia, D., & Rieser, V. (2016). The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes. In 10th International Conference on Language Resources and Evaluation (LR

We present a newly crowd-sourced data set of natural language references to objects anchored in complex urban scenes (In short: The REAL Corpus – Referring Expressions Anchored Language). The REAL corpus contains a collection of images of real-world... Read More about The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes.

How to Talk to Strangers: generating medical reports for first time users (2016)
Presentation / Conference Contribution
Gkatzia, D., Rieser, V., & Lemon, O. (2016). How to Talk to Strangers: generating medical reports for first time users. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ-IEEE.2016.7737739

We propose a novel approach for handling first-time users in the context of automatic report generation from timeseries data in the health domain. Handling first-time users is a common problem for Natural Language Generation (NLG) and interactive... Read More about How to Talk to Strangers: generating medical reports for first time users.

Natural Language Generation enhances human decision-making with uncertain information. (2016)
Presentation / Conference Contribution
Gkatzia, D., Lemon, O., & Rieser, V. (2016, August). Natural Language Generation enhances human decision-making with uncertain information. Presented at 54th Annual Meeting of the Association for Computational Linguistics (ACL) Volume 2 (short papers)

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different information presentations for uncertain data and, for the first time, measure their effects on hu... Read More about Natural Language Generation enhances human decision-making with uncertain information..

From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes (2015)
Presentation / Conference Contribution
Gkatzia, D., Rieser, V., Bartie, P., & Mackaness, W. (2015). From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (1936-1942). http

Predicting the success of referring expressions (RE) is vital for real world applications such as navigation systems. Traditionally, research has focused on studying Referring Expression Generation (REG) in virtual, controlled environments. In this p... Read More about From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes.

Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments (2015)
Presentation / Conference Contribution
Cercas Curry, A., Gkatzia, D., & Rieser, V. (2015). Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments. In Proceedings of the 15th European Workshop on Natural Language Generation (90-94). https://doi.org/10.18653/v1

Referring to landmarks has been identified to lead to improved navigation instructions. However, a previous corpus study suggests that human “wizards” also choose to refer to street names and generate user-centric instructions. In this paper, we cond... Read More about Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments.