13 results

Finding middle ground? Multi-objective Natural Language Generation from time-series data

Conference Proceeding
Gkatzia, D., Hastie, H., & Lemon, O. (2014)
Finding middle ground? Multi-objective Natural Language Generation from time-series data. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers. https://doi.org/10.3115/v1/e14-4041
A Natural Language Generation (NLG) system is able to generate text from nonlinguistic data, ideally personalising the content to a user’s specific needs. In some cases, howev...

The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes

Conference Proceeding
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 (LREC)
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 Anchore...

A Snapshot of NLG Evaluation Practices 2005 - 2014

Conference Proceeding
Gkatzia, D., & Mahamood, S. (2015)
A Snapshot of NLG Evaluation Practices 2005 - 2014. https://doi.org/10.18653/v1/w15-4708
In this paper we present a snapshot of endto-end NLG system evaluations as presented in conference and journal papers1 over the last ten years in order to better understand th...

Natural Language Generation enhances human decision-making with uncertain information.

Conference Proceeding
Gkatzia, D., Lemon, O., & Rieser, V. (2016)
Natural Language Generation enhances human decision-making with uncertain information. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (264-268). https://doi.org/10.18653/v1/P16-2043
Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different information presentati...

From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes

Conference Proceeding
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. https://doi.org/10.18653/v1/d15-1224
Predicting the success of referring expressions (RE) is vital for real world applications such as navigation systems. Traditionally, research has focused on studying Referring...

A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation

Conference Proceeding
Gkatzia, D., Cercas Curry, A., Rieser, V., & Lemon, O. (2015)
A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation. In Proceedings of the 15th European Workshop on Natural Language Generation, 112-113. https://doi.org/10.18653/v1/w15-4720
Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores, such as probabilities. A concrete example of such data is weather data. We w...

Multi-adaptive Natural Language Generation using Principal Component Regression

Conference Proceeding
Gkatzia, D., Hastie, H., & Lemon, O. (2014)
Multi-adaptive Natural Language Generation using Principal Component Regression. In Proceedings of the 8th International Natural Language Generation Conference, 138-142
We present FeedbackGen, a system that uses a multi-adaptive approach to Natural Language Generation. With the term 'multi-adaptive', we refer to a system that is able to adapt...

Commonsense-enhanced Natural Language Generation for Human-Robot Interaction

Conference Proceeding
Gkatzia, D. (in press)
Commonsense-enhanced Natural Language Generation for Human-Robot Interaction
Commonsense is vital for human communication, as it allows us to make inferences without explicitly mentioning the context. Equipping robots with commonsense knowledge would l...

Generating Verbal Descriptions from Medical Sensor Data: A Corpus Study on User Preferences

Conference Proceeding
Gkatzia, D., Rieser, V., Mcsporran, A., Mcgowan, A., Mort, A., & Dewar, M. (2014)
Generating Verbal Descriptions from Medical Sensor Data: A Corpus Study on User Preferences. In BCS Health Informatics Scotland (HIS)
Understanding and interpreting medical sensor data is an essential part of pre-hospital care in medical emergencies, but requires training and previous knowledge. In this pape...

How to Talk to Strangers: generating medical reports for first time users

Conference Proceeding
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...