LibriWASN: A Data Set for Meeting Separation, Diarization, and
  Recognition with Asynchronous Recording Devices
Joerg Schmalenstroeer Tobias Gburrek Reinhold Haeb-Umbach
We present LibriWASN, a data set whose design follows closely the LibriCSS
meeting recognition data set, with the marked difference that the data is
recorded with devices that are randomly positioned on a meeting table and whose
sampling clocks are not synchronized. Nine different devices, five smartphones
with a single recording channel and four microphone arrays, are used to record
a total of 29 channels. Other than that, the data set follows closely the
LibriCSS design: the same LibriSpeech sentences are played back from eight
loudspeakers arranged around a meeting table and the data is organized in
subsets with different percentages of speech overlap. LibriWASN is meant as a
test set for clock synchronization algorithms, meeting separation, diarization
and transcription systems on ad-hoc wireless acoustic sensor networks. Due to
its similarity to LibriCSS, meeting transcription systems developed for the
former can readily be tested on LibriWASN. The data set is recorded in two
different rooms and is complemented with ground-truth diarization information
of who speaks when.