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Full-Text Articles in Engineering
The Impact Of Fuzzy Requirements On Medical Device Software Development, Martin Mchugh, Abder-Rahman Ali, Fergal Mccaffery
The Impact Of Fuzzy Requirements On Medical Device Software Development, Martin Mchugh, Abder-Rahman Ali, Fergal Mccaffery
Conference papers
Any software development project can experience difficulties with unclear or vague requirements. Unfortunately, this problem can be experience two fold in regulated environments such as the medical device software development industry. In the medical device software development industry, development organisations must contend with vague or “fuzzy” both the customer and regulatory bodies. As new requirements are introduced they can have a knock on effect on other requirements. These requirements should be analysed to determine if they are conflicting, cooperative, mutually exclusive and irrelevant. Only when the requirement is classified can a clear method be established as how to integrate that …
Building A Database Of Political Speech Does Culture Matter In Charisma Annotations?, Andrew Hines, Ailbhe Cullen, Naomi Harte
Building A Database Of Political Speech Does Culture Matter In Charisma Annotations?, Andrew Hines, Ailbhe Cullen, Naomi Harte
Conference papers
For both individual politicians and political parties the in- ternet has become a vital tool for self-promotion and the distribution of ideas. The rise of streaming has enabled po- litical debates and speeches to reach global audiences. In this paper, we explore the nature of charisma in political speech, with a view to automatic detection. To this end, we have collected a new database of political speech from YouTube and other on-line resources. Annotation is per- formed both by native listeners, and Amazon Mechanical Turk (AMT) workers. Detailed analysis shows that both la- bel sets are equally reliable. The results …
Robustness And Prediction Accuracy Of Machine Learning For Objective Visual Quality Assessment, Andrew Hines, Paul Kendrick, Adriaan Barri, Manish Narwaria, Judith A. Redi
Robustness And Prediction Accuracy Of Machine Learning For Objective Visual Quality Assessment, Andrew Hines, Paul Kendrick, Adriaan Barri, Manish Narwaria, Judith A. Redi
Conference papers
Machine Learning (ML) is a powerful tool to support the development of objective visual quality assessment metrics, serving as a substitute model for the perceptual mechanisms acting in visual quality appreciation. Nevertheless, the reliability of ML-based techniques within objective quality assessment metrics is often questioned. In this study, the robustness of ML in supporting objective quality assessment is investigated, specifically when the feature set adopted for prediction is suboptimal. A Principal Component Regression based algorithm and a Feed Forward Neural Network are compared when pooling the Structural Similarity Index (SSIM) features perturbed with noise. The neural network adapts better with …
Perceived Audio Quality For Streaming Stereo Music, Andrew Hines, Eoin Gillen, Naomi Harte, Damien Kelly, Jan Skoglund, Anil Kokaram
Perceived Audio Quality For Streaming Stereo Music, Andrew Hines, Eoin Gillen, Naomi Harte, Damien Kelly, Jan Skoglund, Anil Kokaram
Conference papers
Users of audio-visual streaming services expect an ever increasing quality of experience. Channel bandwidth remains a bottleneck commonly addressed with lossy compression schemes for both the video and audio streams. Anecdotal evidence suggests a strongly perceived link between bit rate and quality. This paper presents three audio quality listening experiments using the ITU MUSHRA methodology to assess a number of audio codecs typically used by streaming services. They were assessed for a range of bit rates using three presentation modes: consumer and studio qual- ity headphones and loudspeakers. Our results indicate that with consumer quality headphones, listeners were not differentiating …
Clarification Dialogues For Perception-Based Errors In Situated Human-Computer Dialogues, Niels Schütte, John D. Kelleher, Brian Mac Namee
Clarification Dialogues For Perception-Based Errors In Situated Human-Computer Dialogues, Niels Schütte, John D. Kelleher, Brian Mac Namee
Conference papers
We present an experiment about situated human-computer interaction. Participants interacted with a simulated robot system to complete a series of tasks in a situated environment. Errors were introduced into the robot's perception to produce misunderstandings. We recorded the interactions and attempt to identify strategies the participants used to solve the arising problems.