相关论文: Attention-driven read-aloud technology increases r…
As a common approach to learning English, reading comprehension primarily entails reading articles and answering related questions. However, the complexity of designing effective exercises results in students encountering standardized…
The joint understanding of vision and language has been recently gaining a lot of attention in both the Computer Vision and Natural Language Processing communities, with the emergence of tasks such as image captioning, image-text matching,…
In this paper, we introduce the Reinforced Mnemonic Reader for machine reading comprehension tasks, which enhances previous attentive readers in two aspects. First, a reattention mechanism is proposed to refine current attentions by…
The emergence of mobile eye trackers embedded in next generation smartphones or VR displays will make it possible to trace not only what objects we look at but also the level of attention in a given situation. Exploring whether we can…
This paper explores the effectiveness of Multimodal Large Language models (MLLMs) as assistive technologies for visually impaired individuals. We conduct a user survey to identify adoption patterns and key challenges users face with such…
Despite the plethora of AI-based algorithms developed for anomaly detection in radiology, subsequent integration into clinical setting is rarely evaluated. In this work, we assess the applicability and utility of an AI-based model for brain…
The SmartAbility Android Application recommends Assistive Technology (AT) for people with reduced physical ability, by focusing on the actions (abilities) that can be performed independently. The Application utilises built-in sensor…
Hearing aids are expected to improve speech intelligibility for listeners with hearing impairment. An appropriate amplification fitting tuned for the listener's hearing disability is critical for good performance. The developments of most…
Advances in eye-tracking control for assistive robotic arms provide intuitive interaction opportunities for people with physical disabilities. Shared control has gained interest in recent years by improving user satisfaction through partial…
Autism Spectrum Disorder (ASD) affects children's social and communication abilities, with eye-tracking widely used to identify atypical gaze patterns. While unsupervised clustering can automate the creation of areas of interest for gaze…
Objective: To investigate whether performance (number of correct decisions) of humans supported by a computer alerting tool can be improved by tailoring the tool's alerting threshold (sensitivity/specificity combination) according to user…
When we interact with small screen devices, sometimes we make errors, due to our abilities/disabilities, contextual factors that distract our attention or problems related to the interface. Recovering from these errors may be time consuming…
Accessing visual information is crucial yet challenging for people with low vision due to visual conditions like low visual acuity and limited visual fields. However, unlike blind people, low vision people have and prefer using their…
Affective computing research traditionally focused on labeling a person's emotion as one of a discrete number of classes e.g. happy or sad. In recent times, more attention has been given to continuous affect prediction across dimensions in…
Humans race drones faster than neural networks trained for end-to-end autonomous flight. This may be related to the ability of human pilots to select task-relevant visual information effectively. This work investigates whether neural…
Literacy assessment is an important activity for education administrators across the globe. Typically achieved in a school setting by testing a child's oral reading, it is intensive in human resources. While automatic speech recognition…
We introduced a {\it working memory} augmented adaptive controller in our recent work. The controller uses attention to read from and write to the working memory. Attention allows the controller to read specific information that is relevant…
This paper provides an overview of recent progress in non-intrusive speech intelligibility prediction for hearing aids (HA). We summarize developments in robust acoustic feature extraction, hearing loss modeling, and the use of emerging…
Lip reading aims to predict spoken language by analyzing lip movements. Despite advancements in lip reading technologies, performance degrades when models are applied to unseen speakers due to their sensitivity to variations in visual…
In this study, I explored the impact of Generative AI on learning efficacy in academic reading materials using experimental methods. College-educated participants engaged in three cycles of reading and writing tasks. After each cycle, they…