Defining Ally’s Interactions

A Deep Learning framework to create a personalised interaction between users and a medical pod

Master thesis (2018)

Authors

S.R. Rangarajan Industrial Design Engineering

Contributors

M.S. Kleinsmann (supervisor 1)
A.Q. Beekman (coach)
Faculty
Industrial Design Engineering
Copyright: © 2018 Sathya Rangarajan
Deep Learning Artificial intelligence Design Feature Extraction Design for Interaction Interaction Design User research
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Published Date

29-03-2018

Language

English

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Faculty

Industrial Design Engineering

Abstract

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. A questionnaire to identify the voice characteristics each generation prefers in a medical device, is created. 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 personalised 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 personalisation.