  This paper introduces a large-scale Korean speech dataset, called VOTE400,
that can be used for analyzing and recognizing voices of the elderly people.
The dataset includes about 300 hours of continuous dialog speech and 100 hours
of read speech, both recorded by the elderly people aged 65 years or over. A
preliminary experiment showed that speech recognition system trained with
VOTE400 can outperform conventional systems in speech recognition of elderly
people's voice. This work is a multi-organizational effort led by ETRI and
MINDs Lab Inc. for the purpose of advancing the speech recognition performance
of the elderly-care robots.
