Voice Customization

Abstract

Many digital applications offer avatar customization options, positively affecting user experience. However, the adoption of auditory aspects in avatar customization has often been neglected and may have been understudied for its potential. Inspired by prior research that uncovers end-user’s demands for voice customization, we seek to apply the identified implications into practice and discover enduser’s voice preferences and behavior towards voice customization systems. To this end, we designed and deployed AVOCUS, a web application that enables users to search for specific voices or manipulate voice-related parameters to generate a voice similar to a target voice. Our findings suggest that (1) searching for specific voice using hashtags were perceived to be easy, (2) customized voices generated from voice reflection and voice parameter control functions had high satisfaction, and (3) participants tend to reflect the features of their desired voices when customizing their own voice.

Project Overview

As a follow-up study to our CHI 22 publication, we developed a voice customizing web app and conducted user testing. In this app, users can upload a target voice they wish to resemble, and either upload their own voice or record it directly through the interface. By adjusting the similarity to the target voice and fine-tuning specific attribute values, the app generates a customized voice output within seconds. Although traditional voice generation typically requires AI models and large datasets, this study is significant in presenting an alternative approach that does not rely on such resources.

System Overview