Outputs (45)

Automatically Labeling Cyber Threat Intelligence reports using Natural Language Processing (2023)
Conference Proceeding
Abdi, H., Bagley, S. R., Furnell, S., & Twycross, J. (2023). Automatically Labeling Cyber Threat Intelligence reports using Natural Language Processing. In DocEng ’23 : Proceedings of the 2023 ACM Symposium on Document Engineering. https://doi.org/10.1145/3573128.3609348

Attribution provides valuable intelligence in the face of Advanced Persistent Threat (APT) attacks. By accurately identifying the culprits and actors behind the attacks, we can gain more insights into their motivations, capabilities, and potential fu... Read More about Automatically Labeling Cyber Threat Intelligence reports using Natural Language Processing.

Hyper-Stacked: Scalable and Distributed Approach to AutoML for Big Data (2023)
Conference Proceeding
Dave, R., Angarita-Zapata, J. S., & Triguero, I. (2023). Hyper-Stacked: Scalable and Distributed Approach to AutoML for Big Data. In Machine Learning and Knowledge Extraction (82-102). https://doi.org/10.1007/978-3-031-40837-3_6

The emergence of Machine Learning (ML) has altered how researchers and business professionals value data. Applicable to almost every industry, considerable amounts of time are wasted creating bespoke applications and repetitively hand-tuning models t... Read More about Hyper-Stacked: Scalable and Distributed Approach to AutoML for Big Data.

LABERT: A Combination of Local Aggregation and Self-Supervised Speech Representation Learning for Detecting Informative Hidden Units in Low-Resource ASR Systems (2023)
Conference Proceeding
Fatehi, K., & Kucukyilmaz, A. (2023). LABERT: A Combination of Local Aggregation and Self-Supervised Speech Representation Learning for Detecting Informative Hidden Units in Low-Resource ASR Systems. In Interspeech 2023

With advances in deep learning methodologies, Automatic Speech Recognition (ASR) systems have seen impressive results. However, ASR in Low-Resource Environments (LREs) are challenged by a lack of training data for the specific target domain. We propo... Read More about LABERT: A Combination of Local Aggregation and Self-Supervised Speech Representation Learning for Detecting Informative Hidden Units in Low-Resource ASR Systems.

RoboClean: Contextual Language Grounding for Human-Robot Interactions in Specialised Low-Resource Environments (2023)
Conference Proceeding
Fuentes, C., Porcheron, M., & Fischer, J. E. (2023). RoboClean: Contextual Language Grounding for Human-Robot Interactions in Specialised Low-Resource Environments. In Proceedings of the 5th International Conference on Conversational User Interfaces (CUI '23). https://doi.org/10.1145/3571884.3597137

Building effective voice interfaces for the instruction of service robots in specialised environments is difficult due to the local knowledge of workers, such as specific terminology for objects and space, leading to limited data to train language mo... Read More about RoboClean: Contextual Language Grounding for Human-Robot Interactions in Specialised Low-Resource Environments.

Generative AI Considered Harmful (2023)
Conference Proceeding
Fischer, J. E. (2023). Generative AI Considered Harmful. In Proceedings of the 5th International Conference on Conversational User Interfaces (CUI '23). https://doi.org/10.1145/3571884.3603756

The recent months have seen an explosion of interest, hype, and concern about generative AI, driven by the release of ChatGPT. In this article I seek to explicate some potential and actual harms of the engineering and use of generative AI such as Cha... Read More about Generative AI Considered Harmful.

Sequential Rule Mining for Automated Design of Meta-heuristics (2023)
Conference Proceeding
Meng, W., & Qu, R. (2023). Sequential Rule Mining for Automated Design of Meta-heuristics. In GECCO’23 Companion: Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (1727-1735). https://doi.org/10.1145/3583133.3596303

With a recently defined AutoGCOP framework, the design of local search algorithms can be defined as the composition of the basic elementary algorithmic components. These compositions into the best algorithms thus retain useful knowledge of effective... Read More about Sequential Rule Mining for Automated Design of Meta-heuristics.

Using a Knowledge Café approach as a public engagement activity for raising awareness of data protection issues in robotics for health and social care (2023)
Conference Proceeding
Piskopani, A. M., Webb, H., & Caleb-Solly, P. (2023). Using a Knowledge Café approach as a public engagement activity for raising awareness of data protection issues in robotics for health and social care. In TAS '23: Proceedings of the First International Symposium on Trustworthy Autonomous Systems (1-5). https://doi.org/10.1145/3597512.3599700

Robotics and Artificial Intelligence (RAI) offers the opportunity to ameliorate the quality of life for people with health issues. However, there are still considerable barriers linked to the lack of acceptance of these technologies, particularly as... Read More about Using a Knowledge Café approach as a public engagement activity for raising awareness of data protection issues in robotics for health and social care.

Co-creating Museum Robots With People That Are Autistic and/or Have Learning Disabilities (2023)
Conference Proceeding
Cameron, H., Story, M., Reyes-Cruz, G., & Galvez Trigo, M. J. (2023). Co-creating Museum Robots With People That Are Autistic and/or Have Learning Disabilities. In TAS '23: Proceedings of the First International Symposium on Trustworthy Autonomous Systems (1-5). https://doi.org/10.1145/3597512.3597525

The integration of robots into everyday life is an increasingly common and mundane phenomena. Understanding how people regard and interact with these robots is a rapidly growing area of study, however, there is limited consideration of the attitudes... Read More about Co-creating Museum Robots With People That Are Autistic and/or Have Learning Disabilities.

TAME Pain: Trustworthy AssessMEnt of Pain from Speech and Audio for the Empowerment of Patients (2023)
Conference Proceeding
Schneiders, E., Williams, J., Farahi, A., Seabrooke, T., Vigneswaran, G., Bautista, J. R., …Piskopani, A. M. (2023). TAME Pain: Trustworthy AssessMEnt of Pain from Speech and Audio for the Empowerment of Patients. In TAS'23: Proceedings of the First International Symposium on Trustworthy Autonomous Systems. https://doi.org/10.1145/3597512.3597513

Precise pain assessment is crucial for medical professionals to provide appropriate treatment. However, not every patient can verbalise the experienced pain for various reasons (e.g., speech disorders or language barriers). In these cases, medical pr... Read More about TAME Pain: Trustworthy AssessMEnt of Pain from Speech and Audio for the Empowerment of Patients.

TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals (2023)
Conference Proceeding
Schneiders, E., Chamberlain, A., Fischer, J. E., Benford, S., Castle-Green, S., Ngo, V., …Mills, D. (2023). TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals. In TAS ‘23: Proceedings of The First International Symposium on Trustworthy Autonomous Systems 11-12 July 2023 Edinburgh, UK. https://doi.org/10.1145/3597512.3597517

Cat Royale is an artist-led exploration of trustworthy autonomous systems (TAS) created by the TAS Hub's creative ambassadors Blast Theory. A small community of cats inhabits a purpose built 'cat utopia' at the centre of which a robot arm tries to en... Read More about TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals.