10 citations · 43 across the 26 of their papers we have counts for
27 papers
DRONEAUDIONET: Noise Suppression for Drone Audition-based Search and Rescue
Chitralekha Gupta, Soundarya Ramesh, Yifei Luo +1
Microphones mounted on UAVs enable aerial acoustic scene analysis applications such as search-and-rescue, wildlife monitoring, and industrial inspection. However, drone rotor noise…
Beyond Descriptions: A Generative Scene2Audio Framework for Blind and Low-Vision Users to Experience Vista Landscapes
Chitralekha Gupta, Jing Peng, Ashwin Ram +3
Current scene perception tools for Blind and Low Vision (BLV) individuals rely on spoken descriptions but lack engaging representations of visually pleasing distant environmental l…
VisceroHaptics: Investigating the Effects of Gut-based Audio-Haptic Feedback on Gastric Feelings and Gastric Interoceptive Behavior
Mia Huong Nguyen, Moritz Alexander Messerschmidt, Jochen Huber +1
Gastric interoception influences eating behavior and emotions, making its modulation valuable for healthcare and human-computer-interaction applications. However, whether gastric i…
DroneAudioset: An Audio Dataset for Drone-based Search and Rescue
Chitralekha Gupta, Soundarya Ramesh, Praveen Sasikumar +2
Unmanned Aerial Vehicles (UAVs) or drones, are increasingly used in search and rescue missions to detect human presence. Existing systems primarily leverage vision-based methods wh…
Towards Temporally Explainable Dysarthric Speech Clarity Assessment
Seohyun Park, Chitralekha Gupta, Michelle Kah Yian Kwan +3
Dysarthria, a motor speech disorder, affects intelligibility and requires targeted interventions for effective communication. In this work, we investigate automated mispronunciatio…
EmoSign: A Multimodal Dataset for Understanding Emotions in American Sign Language
Phoebe Chua, Cathy Mengying Fang, Takehiko Ohkawa +3
Unlike spoken languages where the use of prosodic features to convey emotion is well studied, indicators of emotion in sign language remain poorly understood, creating communicatio…
Perspectives on Capturing Emotional Expressiveness in Sign Language
Phoebe Chua, Cathy Mengying Fang, Yasith Samaradivakara +2
Significant advances have been made in our ability to understand and generate emotionally expressive content such as text and speech, yet comparable progress in sign language techn…
Factually: Exploring Wearable Fact-Checking for Augmented Truth Discernment
Chitralekha Gupta, Hanjun Wu, Praveen Sasikumar +3
Wearable devices are transforming human capabilities by seamlessly augmenting cognitive functions. In this position paper, we propose a voice-based, interactive learning companion…
Navigating the State of Cognitive Flow: Context-Aware AI Interventions for Effective Reasoning Support
Dinithi Dissanayake, Suranga Nanayakkara
Flow theory describes an optimal cognitive state where individuals experience deep focus and intrinsic motivation when a task's difficulty aligns with their skill level. In AI-augm…
Broadening Participation through Physical Computing: Replicating Sensor-Based Programming Workshops for Rural Students in Sri Lanka
Poornima Meegammana, Hussel Suriyaarachchi, Paul Denny +1
In today's digital world, computing education offers critical opportunities, yet systemic inequities exclude under-represented communities, especially in rural, under-resourced reg…
The Goldilocks Time Window for Proactive Interventions in Wearable AI Systems
Cathy Mengying Fang, Wazeer Zulfikar, Yasith Samaradivakara +2
As AI systems become increasingly integrated into our daily lives and into wearable form factors, there's a fundamental tension between their potential to proactively assist us and…
Mirai: A Wearable Proactive AI "Inner-Voice" for Contextual Nudging
Cathy Mengying Fang, Yasith Samaradivakara, Pattie Maes +1
People often find it difficult to turn their intentions into real actions -- a challenge that affects both personal growth and mental well-being. While established methods like cog…
Tailored Real-time AR Captioning Interface for Enhancing Learning Experience of Deaf and Hard-of-Hearing (DHH) Students
Yasith Samaradivakara, Asela Pathirage, Thavindu Ushan +4
Deaf and hard-of-hearing (DHH) students face significant challenges in specialized educational settings, such as limited exposure to written and spoken language, a lack of tailored…
Investigating the Use of Productive Failure as a Design Paradigm for Learning Introductory Python Programming
Hussel Suriyaarachchi, Paul Denny, Suranga Nanayakkara
Productive Failure (PF) is a learning approach where students initially tackle novel problems targeting concepts they have not yet learned, followed by a consolidation phase where…
Motion as Emotion: Detecting Affect and Cognitive Load from Free-Hand Gestures in VR
Phoebe Chua, Prasanth Sasikumar, Yadeesha Weerasinghe +1
Affect and cognitive load influence many user behaviors. In this paper, we propose Motion as Emotion, a novel method that utilizes fine differences in hand motion to recognise affe…
MorphFader: Enabling Fine-grained Controllable Morphing with Text-to-Audio Models
Purnima Kamath, Chitralekha Gupta, Suranga Nanayakkara
Sound morphing is the process of gradually and smoothly transforming one sound into another to generate novel and perceptually hybrid sounds that simultaneously resemble both. Rece…
EMO-KNOW: A Large Scale Dataset on Emotion and Emotion-cause
Mia Huong Nguyen, Yasith Samaradivakara, Prasanth Sasikumar +2
Emotion-Cause analysis has attracted the attention of researchers in recent years. However, most existing datasets are limited in size and number of emotion categories. They often…
Example-Based Framework for Perceptually Guided Audio Texture Generation
Purnima Kamath, Chitralekha Gupta, Lonce Wyse +1
Controllable generation using StyleGANs is usually achieved by training the model using labeled data. For audio textures, however, there is currently a lack of large semantically l…
VR.net: A Real-world Dataset for Virtual Reality Motion Sickness Research
Elliott Wen, Chitralekha Gupta, Prasanth Sasikumar +5
Researchers have used machine learning approaches to identify motion sickness in VR experience. These approaches demand an accurately-labeled, real-world, and diverse dataset for h…
Towards Controllable Audio Texture Morphing
Chitralekha Gupta, Purnima Kamath, Yize Wei +3
In this paper, we propose a data-driven approach to train a Generative Adversarial Network (GAN) conditioned on "soft-labels" distilled from the penultimate layer of an audio class…
Using Sensor-Based Programming to Improve Self-Efficacy and Outcome Expectancy for Students from Underrepresented Groups
Hussel Suriyaarachchi, Alaeddin Nassani, Paul Denny +1
Knowledge of programming and computing is becoming increasingly valuable in today's world, and thus it is crucial that students from all backgrounds have the opportunity to learn.…
Striving for Authentic and Sustained Technology Use In the Classroom: Lessons Learned from a Longitudinal Evaluation of a Sensor-based Science Education Platform
Yvonne Chua, Sankha Cooray, Juan Pablo Forero Cortes +19
Technology integration in educational settings has led to the development of novel sensor-based tools that enable students to measure and interact with their environment. Although…
Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering
Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen +3
Retrieval Augment Generation (RAG) is a recent advancement in Open-Domain Question Answering (ODQA). RAG has only been trained and explored with a Wikipedia-based external knowledg…
Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering
Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen +1
In this paper, we illustrate how to fine-tune the entire Retrieval Augment Generation (RAG) architecture in an end-to-end manner. We highlighted the main engineering challenges tha…