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ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments (2022)
Conference Proceeding
Fatehi, K., Torres, M. T., & Kucukyilmaz, A. (2022). ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments. In Proceedings of Interspeech 2022 (3523-3527). https://doi.org/10.21437/Interspeech.2022-10270

Recent improvements in Automatic Speech Recognition (ASR) systems obtain extraordinary results. However, there are specific domains where training data can be either limited or not representative enough, which are known as Low-Resource Environments (... Read More about ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments.

A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation (2022)
Journal Article
Borsci, S., Schmettow, M., Malizia, A., Chamberlain, A., & van der Velde, F. (2022). A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation. Personal and Ubiquitous Computing, https://doi.org/10.1007/s00779-022-01690-0

The Bot Usability Scale (BUS) is a standardised tool to assess and compare the satisfaction of users after interacting with chatbots to support the development of usable conversational systems. The English version of the 15-item BUS scale (BUS-15) wa... Read More about A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation.

Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning (2022)
Conference Proceeding
Serhan, B., Pandya, H., Kucukyilmaz, A., & Neumann, G. (2022). Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning. In IEEE International Conference on Robotics and Automation (ICRA 2022) (1513-1519). https://doi.org/10.1109/ICRA46639.2022.9811645

Efficient robotic manipulation of objects for sorting and searching often rely upon how well the objects are perceived and the available grasp poses. The challenge arises when the objects are irregular, have similar visual features (e.g., textureless... Read More about Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning.

ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies (2021)
Conference Proceeding
Galvez Trigo, M. J., Porcheron, M., Egede, J., Fischer, J. E., Hazzard, A., Greenhalgh, C., …Valstar, M. (2021). ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies. In Proceedings of CUI 2021 : Conversational User Interfaces. https://doi.org/10.1145/3469595.3469621

We present ALTCAI, a Wizard of Oz Embodied Conversational Agent that has been developed to explore the use of interactive agents as an effective and engaging tool for delivering health and well-being advice to expectant and nursing mothers in Nigeria... Read More about ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies.

Teachers’ Perspectives on the Adoption of an Adaptive Learning System Based on Multimodal Affect Recognition for Students with Learning Disabilities and Autism (2021)
Conference Proceeding
Standen, P. J., Brown, D. J., Kwiatkowska, G. M., Belmonte, M. K., Galvez Trigo, M. J., Boulton, H., …Traversi, M. (2021). Teachers’ Perspectives on the Adoption of an Adaptive Learning System Based on Multimodal Affect Recognition for Students with Learning Disabilities and Autism. In R. A. Sottilare, & J. Schwarz (Eds.), Adaptive Instructional Systems. Design and Evaluation : Third International Conference, AIS 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part I. https://doi.org/10.1007/978-3-030-77857-6

Adoption of e-learning for those with special needs lags that for mainstream learners. Not much is known about barriers and facilitators that drive this disparity. The present study used focus groups and interviews to collect the views of 21 teachers... Read More about Teachers’ Perspectives on the Adoption of an Adaptive Learning System Based on Multimodal Affect Recognition for Students with Learning Disabilities and Autism.

Improving Uncertainty Estimation With Semi-supervised Deep Learning for COVID-19 Detection Using Chest X-ray Images (2021)
Journal Article
Calderon-Ramirez, S., Yang, S., Moemeni, A., Colreavy-Donnelly, S., Elizondo, D. A., Oala, L., …Molina-Cabello, M. A. (2021). Improving Uncertainty Estimation With Semi-supervised Deep Learning for COVID-19 Detection Using Chest X-ray Images. IEEE Access, 9, 85442 - 85454. https://doi.org/10.1109/ACCESS.2021.3085418

In this work we implement a COVID-19 infection detection system based on chest Xray images with uncertainty estimation. Uncertainty estimation is vital for safe usage of computer aided diagnosis tools in medical applications. Model estimations with h... Read More about Improving Uncertainty Estimation With Semi-supervised Deep Learning for COVID-19 Detection Using Chest X-ray Images.

Intelligent control of exoskeletons through a novel learning-from-demonstration method (2020)
Presentation / Conference
Ugur, E., Samur, E., Ugurlu, B., Erol Barkana, D., Kucukyilmaz, A., & Bebek, O. (2020, September). Intelligent control of exoskeletons through a novel learning-from-demonstration method. Poster presented at Cybathlon Symposium 2020, Zurich, Switzerland

We present a novel concept that enables the intelligent and adaptive control of exoskeletons through exploiting our state-of-the-art learning from demonstration (LfD) method, namely Conditional Neural Movement Primitives (CNMPs) [1], on our integrate... Read More about Intelligent control of exoskeletons through a novel learning-from-demonstration method.

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling (2019)
Journal Article
Gibbs, J., French, A., Murchie, E., Wells, D., Pound, M., & Pridmore, T. (2020). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(6), 1907-1917. https://doi.org/10.1109/TCBB.2019.2896908

Plant phenotyping is the quantitative description of a plant’s physiological, biochemical and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based... Read More about Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling.

Deep learning approaches to aircraft maintenance, repair and overhaul: a review (2018)
Conference Proceeding
Rengasami, D., Morvan, H., & Patrocinio Figueredo, G. (2018). Deep learning approaches to aircraft maintenance, repair and overhaul: a review. In 21st IEEE International Conference on Intelligent Transportation Systemshttps://doi.org/10.1109/ITSC.2018.8569502

The use of sensor technology constantly gathering aircrafts' status data has promoted the rapid development of data-driven solutions in aerospace engineering. These methods assist, for instance, with determining appropriate actions for aircraft maint... Read More about Deep learning approaches to aircraft maintenance, repair and overhaul: a review.

Hyper-heuristics: theory and applications (2018)
Book
Pillay, N., & Qu, R. (2018). Hyper-heuristics: theory and applications. Cham, Switzerland: Springer Nature. doi:10.1007/978-3-319-96514-7

This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, pro... Read More about Hyper-heuristics: theory and applications.

Model checking for Coalition Announcement Logic (2018)
Book Chapter
Galimullin, R., Alechina, N., & van Ditmarsch, H. (2018). Model checking for Coalition Announcement Logic. In F. Trollmann, & A. Turhan (Eds.), KI 2018: Advances in Artificial Intelligence, 41st German Conference on AI, Berlin, Germany, September 24–28, 2018, Proceedings (11-23). Cham: Springer Publishing Company. https://doi.org/10.1007/978-3-030-00111-7_2

Coalition Announcement Logic (CAL) studies how a group of agents can enforce a certain outcome by making a joint announcement, regardless of any announcements made simultaneously by the opponents. The logic is useful to model imperfect information ga... Read More about Model checking for Coalition Announcement Logic.