Highly-Reverberant Real Environment database: HRRE
Juan Pablo Escudero, Víctor Poblete, José Nóvoa, Jorge Wuth, Josué Fredes, Rodrigo Mahú, Richard M. Stern, Néstor Becerra Yoma · arXiv (Cornell University) · 2018
Speech recognition in highly-reverberant real environments remains a major challenge. An evaluation dataset for this task is needed. This report describes the generation of the Highly-Reverberant Real Environment database (HRRE). This database contains 13.4 hours of data recorded in real reverberant environments and consists of 20 different testing conditions which consider a wide range of reverberation times and speaker-to-microphone distances. These evaluation sets were generated by re-recording the clean test set of the Aurora-4 database which corresponds to five loudspeaker-microphone distances in four reverberant conditions.