Get It Right: Improving Comprehensibility with Adaptable Speech Expression of a Humanoid Service Robot
This addresses the need for adaptable communication in human-robot interaction for public service customers, but it appears incremental as it builds on existing translation and simplification methods.
The study tackled the problem of improving comprehensibility of complex information provided by a humanoid service robot in public settings by proposing an application architecture that allows translation into easy language or other spoken languages, but no concrete results or numbers are reported.
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.