Defining Ally’s interactions
Sep 2017 - ongoing
A Deep Learning framework to create a personalised interaction between users and a medical pod
Ally, is an intelligent, voice activated medical device concept that users talk to on a routine basis to log details regarding their health and well-being. The goal of this thesis is to create a personalised interaction between users and Ally. The user group is segregated into three generations; Baby Boomers, Generation X and Millennials. A digital prototype of Ally is used to understand how different generations interact with Ally.
The results from the user test and questionnaire are used to design a Deep Learning framework to generate a WaveNet TTS voice. This framework is a foundation for a personalized interaction between Ally and users, based on the generation they belong to. By creating a framework to cater to specific generations, this model sets the ground rules for personalization.
Name: Sathya Ranjani Rangarajan
Partners: Philips, Hartstichting
Mentors: Maaike Kleinsmann, Quiel Beekman
Master: Design For Interaction