RoboCup@Home spoken corpus: Using robotic competitions for gathering datasets

Abstract

The definition of high quality datasets for benchmarking single components and entire systems in intelligent robots is a fundamental task for developing, testing and comparing different technical solutions. In this paper, we describe the methodology adopted for the acquisition and the creation of a spoken corpus for domestic and service robots. The corpus has been inspired by and acquired in the RoboCup@Home setting, with the involvement of RoboCup@Home participants. The annotated data set is publicly available for developing, testing and comparing speech understanding functionalities of domestic and service robots, not only for teams involved in RoboCup@Home or in other competitions, but also for research groups active in the field. We regard the construction of the dataset as a first step towards a full benchmarking methodology for spoken language interaction in service robotics.