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TaskMaster: A Novel Cross-platform Task-based Spoken Dialogue System for Human-Robot Interaction (2023)
Conference Proceeding
Strathearn, C., Yu, Y., & Gkatzia, D. (2023). TaskMaster: A Novel Cross-platform Task-based Spoken Dialogue System for Human-Robot Interaction. In Proceedings of The Joint CUI and HRI Workshop at HRI 2023

The most effective way of communication between humans and robots is through natural language communication. However, there are many challenges to overcome before robots can effectively converse in order to collaborate and work together with humans.... Read More about TaskMaster: A Novel Cross-platform Task-based Spoken Dialogue System for Human-Robot Interaction.

Responsible Design & Evaluation of a Conversational Agent for a National Careers Service (2023)
Conference Proceeding
Wilson, M., Cruickshank, P., Gkatzia, D., & Robertson, P. (in press). Responsible Design & Evaluation of a Conversational Agent for a National Careers Service.

This PhD project applies a research-through-design approach to the development of a conversational agent for a national career service for young people. This includes addressing practical, interactional and ethical aspects of the system. For each asp... Read More about Responsible Design & Evaluation of a Conversational Agent for a National Careers Service.

Barriers and enabling factors for error analysis in NLG research (2023)
Journal Article
Van Miltenburg, E., Clinciu, M., Dušek, O., Gkatzia, D., Inglis, S., Leppänen, L., …Wen, L. (2023). Barriers and enabling factors for error analysis in NLG research. Northern European Journal of Language Technology, 9(1), https://doi.org/10.3384/nejlt.2000-1533.2023.4529

Earlier research has shown that few studies in Natural Language Generation (NLG) evaluate their system outputs using an error analysis, despite known limitations of automatic evaluation metrics and human ratings. This position paper takes the stance... Read More about Barriers and enabling factors for error analysis in NLG research.

Most NLG is Low-Resource: here's what we can do about it (2022)
Conference Proceeding
Howcroft, D. M., & Gkatzia, D. (2022). Most NLG is Low-Resource: here's what we can do about it. In Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM) (336-350)

Many domains and tasks in natural language generation (NLG) are inherently 'low-resource', where training data, tools and linguistic analyses are scarce. This poses a particular challenge to researchers and system developers in the era of machine-lea... Read More about Most NLG is Low-Resource: here's what we can do about it.

A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue (2022)
Book Chapter
Strathearn, C., & Gkatzia, D. (2023). A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue. In M. Abbas (Ed.), Analysis and Application of Natural Language and Speech Processing (123-144). Cham: Springer. https://doi.org/10.1007/978-3-031-11035-1_6

This paper argues that future dialogue systems must retrieve relevant information from multiple structured and unstructured data sources in order to generate natural and informative responses as well as exhibit commonsense capabilities and flexibilit... Read More about A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue.

Multi3Generation: Multi-task, Multilingual, Multi-Modal Language Generation (2022)
Presentation / Conference
Barreiro, A., de Souza, J. G., Gatt, A., Bhatt, M., Lloret, E., Erdem, A., …Alhasani, M. (2022, June). Multi3Generation: Multi-task, Multilingual, Multi-Modal Language Generation. Poster presented at 23rd Annual Conference of the European Association for Machine Translation (EAMT 2022), Ghent, Belgium

This paper presents the Multitask, Multilingual, Multimodal Language Generation COST Action – Multi3Generation (CA18231), an interdisciplinary network of research groups working on different aspects of language generation. This "metapaper" will serve... Read More about Multi3Generation: Multi-task, Multilingual, Multi-Modal Language Generation.

Opportunities and risks in the use of AI in career development practice (2022)
Journal Article
Wilson, M., Robertson, P., Cruickshank, P., & Gkatzia, D. (2022). Opportunities and risks in the use of AI in career development practice. Journal of the National Institute for Career Education and Counselling, 48(1), 48-57. https://doi.org/10.20856/jnicec.4807

The Covid-19 pandemic required many aspects of life to move online. This accelerated a broader trend for increasing use of ICT and AI, with implications for both the world of work and career development. This article explores the potential benefits a... Read More about Opportunities and risks in the use of AI in career development practice.

Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems (2021)
Conference Proceeding
Strathearn, C., & Gkatzia, D. (2021). Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems. In Proceedings of the 14th International Conference on Natural Language Generation (46-47)

Conversational systems aim to generate responses that are accurate, relevant and engaging, either through utilising neural end-to-end models or through slot filling. Human-to-human conversations are enhanced by not only the latest utterance of the in... Read More about Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems.

The Task2Dial Dataset: A Novel Dataset for Commonsense-enhanced Task-based Dialogue Grounded in Documents (2021)
Conference Proceeding
Strathearn, C., & Gkatzia, D. (2021). The Task2Dial Dataset: A Novel Dataset for Commonsense-enhanced Task-based Dialogue Grounded in Documents. In Proceedings of The Fourth International Conference on Natural Language and Speech Processing (ICNLSP 2021) (242-251)

This paper describes the Task2Dial dataset, a novel dataset of document-grounded task-based dialogues in the food preparation domain , where an Information Giver (IG) provides instructions to an Information Follower (IF) so that the latter can succes... Read More about The Task2Dial Dataset: A Novel Dataset for Commonsense-enhanced Task-based Dialogue Grounded in Documents.

Underreporting of errors in NLG output, and what to do about it (2021)
Conference Proceeding
van Miltenburg, E., Clinciu, M., Dušek, O., Gkatzia, D., Inglis, S., Leppänen, L., …Wen, L. (2021). Underreporting of errors in NLG output, and what to do about it. In Proceedings of the 14th International Conference on Natural Language Generation (140-153)

We observe a severe under-reporting of the different kinds of errors that Natural Language Generation systems make. This is a problem, because mistakes are an important indicator of where systems should still be improved. If authors only report overa... Read More about Underreporting of errors in NLG output, and what to do about it.

CAPE: Context-Aware Private Embeddings for Private Language Learning (2021)
Conference Proceeding
Plant, R., Gkatzia, D., & Giuffrida, V. (2021). CAPE: Context-Aware Private Embeddings for Private Language Learning. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (7970-7978)

Neural language models have contributed to state-of-the-art results in a number of downstream applications including sentiment analysis, intent classification and others. However, obtaining text representations or embeddings using these models risks... Read More about CAPE: Context-Aware Private Embeddings for Private Language Learning.

The Task2Dial Dataset (2021)
Dataset
Gkatzia, D., & Strathearn, C. (2021). The Task2Dial Dataset. [Dataset]

URL: https://huggingface.co/datasets/cstrathe435/Task2Dial

It's Common Sense, isn't it? Demystifying Human Evaluations in Commonsense-enhanced NLG systems (2021)
Conference Proceeding
Mahamood, S., Clinciu, M., & Gkatzia, D. (2021). It's Common Sense, isn't it? Demystifying Human Evaluations in Commonsense-enhanced NLG systems. In Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)

Common sense is an integral part of human cognition which allows us to make sound decisions , communicate effectively with others and interpret situations and utterances. Endowing AI systems with commonsense knowledge capabilities will help us get cl... Read More about It's Common Sense, isn't it? Demystifying Human Evaluations in Commonsense-enhanced NLG systems.

"What's this?" Comparing Active learning Strategies for Concept Acquisition in HRI (2021)
Conference Proceeding
Belvedere, F., & Gkatzia, D. (2021). "What's this?" Comparing Active learning Strategies for Concept Acquisition in HRI. In HRI '21 Companion: Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (205-209). https://doi.org/10.1145/3434074.3447160

Social robotics aim to equip robots with the ability to exhibit socially intelligent behaviour while interacting in a face-to-face context with human partners. An important aspect of face-to-face social interaction includes the efficient recognition... Read More about "What's this?" Comparing Active learning Strategies for Concept Acquisition in HRI.

Generating Unambiguous and Diverse Referring Expressions   (2020)
Journal Article
Panagiaris, N., Hart, E., & Gkatzia, D. (2021). Generating Unambiguous and Diverse Referring Expressions  . Computer Speech and Language, 68, Article 101184. https://doi.org/10.1016/j.csl.2020.101184

Neural Referring Expression Generation (REG) models have shown promising results in generating expressions which uniquely describe visual objects. However, current REG models still lack the ability to produce diverse and unambiguous referring express... Read More about Generating Unambiguous and Diverse Referring Expressions  .

Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definition (2020)
Conference Proceeding
Howcroft, D., Belz, A., Clinciu, M., Gkatzia, D., Hasan, S. A., Mahamood, S., …Rieser, V. (2020). Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definition. In Proceedings of the 13th International Conference on Natural Language Generation (169-182)

Human assessment remains the most trusted form of evaluation in NLG, but highly diverse approaches and a proliferation of different quality criteria used by researchers make it difficult to compare results and draw conclusions across papers, with adv... Read More about Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definition.

Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training (2020)
Conference Proceeding
Panagiaris, N., Hart, E., & Gkatzia, D. (2020). Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training. In Proceedings of the 13th International Conference on Natural Language Generation (41-51)

In this paper we consider the problem of optimizing neural Referring Expression Generation (REG) models with sequence level objectives. Recently reinforcement learning (RL) techniques have been adopted to train deep end-to-end systems to directly opt... Read More about Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training.

Second Workshop on Natural Language Generation for Human-Robot Interaction (2020)
Conference Proceeding
Buschmeier, H., Ellen Foster, M., & Gkatzia, D. (2020). Second Workshop on Natural Language Generation for Human-Robot Interaction. In HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (646-647). https://doi.org/10.1145/3371382.3374853

This workshop is the second in a series bringing together the Natural Language Generation and Human-Robot Interaction communities to discuss topics of mutual interest with the goal of developing an HRI-inspired NLG shared task. The workshop website i... Read More about Second Workshop on Natural Language Generation for Human-Robot Interaction.

Commonsense-enhanced Natural Language Generation for Human-Robot Interaction (2020)
Conference Proceeding
Gkatzia, D. (2020). Commonsense-enhanced Natural Language Generation for Human-Robot Interaction. In 2nd Workshop on Natural Language Generation for Human-Robot Interaction (HRI 2020)

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.