F. Kawsar
27 records found
1
Authored
Conversational agents are increasingly becoming digital partners in our everyday computational experiences. Although rich, and fresh in content, they are oblivious to users’ locality beyond geospatial weather and traffic conditions. We introduce conversational agents that are ...
AudiDoS
Real-time denial-of-service adversarial attacks on deep audio models
Deep learning has enabled personal and IoT devices to rethink microphones as a multi-purpose sensor for understanding conversation and the surrounding environment. This resulted in a proliferation of Voice Controllable Systems (VCS) around us. The increasing popularity of such ...
Conversational agents are increasingly becoming digital partners of our everyday computing experiences offering a variety of purposeful information and utility services. Although rich on competency, these agents are entirely oblivious to their users' situational and emotional ...
The Internet of Things has become a key enabling technology for data-intensive research across universities and private organisations alike. However, the recent introduction of the General Data Protection Regulation (GDPR) in Europe has raised concerns that the GDPR might hamp ...
Demo abstract
ESense - Open Earable Platform for Human Sensing
We present eSense - an open and multi-sensory in-ear wearable platform for personal-scale behaviour analytics. eSense is a true wireless stereo (TWS) earbud and supports dual-mode Bluetooth and Bluetooth Low Energy. It i ...
In this paper, we explore audio and kinetic sensing on earable devices with the commercial on-the-shelf form factor. For the study, we prototyped earbud devices with a 6-axis inertial measurement unit and a microphone. We systematically investigate the differential characteris ...
Mindful interruptions
A lightweight system for managing interruptibility onwearables
We propose a cross-modal approach for conversational well-being monitoring with a multi-sensory earable. It consists of motion, audio, and BLE models on earables. Using the IMU sensor, the microphone, and BLE scanning, the models detect speaking activities, stress and emotion, ...