  We present a speech data corpus that simulates a "dinner party" scenario
taking place in an everyday home environment. The corpus was created by
recording multiple groups of four Amazon employee volunteers having a natural
conversation in English around a dining table. The participants were recorded
by a single-channel close-talk microphone and by five far-field 7-microphone
array devices positioned at different locations in the recording room. The
dataset contains the audio recordings and human labeled transcripts of a total
of 10 sessions with a duration between 15 and 45 minutes. The corpus was
created to advance in the field of noise robust and distant speech processing
and is intended to serve as a public research and benchmarking data set.
