Get It Right: Improving Comprehensibility with Adaptable Speech Expression of a Humanoid Service Robot

TL;DR

This paper presents an application architecture for humanoid robots that enhances communication by translating complex information into simpler language or other languages, improving user understanding in public service contexts.

Contribution

It introduces an adaptable speech expression system for humanoid robots that personalizes communication based on individual user needs and language preferences.

Findings

Improved intelligibility of robot communication in public settings

Successful implementation of language translation and simplification features

Enhanced user experience through personalized interaction

Abstract

As humanoid service robots are becoming more and more perceptible in public service settings for instance as a guide to welcome visitors or to explain a procedure to follow, it is desirable to improve the comprehensibility of complex issues for human customers and to adapt the level of difficulty of the information provided as well as the language used to individual requirements. This work examines a case study using a humanoid social robot Pepper performing support for customers in a public service environment offering advice and information. An application architecture is proposed that improves the intelligibility of the information received by providing the possibility to translate this information into easy language and/or into another spoken language.