COSINE - A corpus of multi-party COnversational Speech In Noisy Environments

Authors:
Alex Stupakov;Evan Hanusa;Jeff Bilmes;Dieter Fox
Affiliations:
Department of Electrical Engineering, University of Washington, Seattle, USA;Department of Electrical Engineering, University of Washington, Seattle, USA;Department of Electrical Engineering, University of Washington, Seattle, USA;Department of Electrical Engineering, University of Washington, Seattle, USA
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Abstract

We present an overview of the data collection and transcription efforts for the COnversational Speech In Noisy Environments (COSINE) corpus. The corpus is a set of multi-party conversations recorded in real world environments with background noise that can be used to train noise-robust speech recognition systems. We explain the motivation for creating such a corpus and describe the resulting audio recordings and transcriptions that comprise the corpus. These recordings include a 4-channel array and close-talking, far-field, and throat microphones on separate synchronized channels, allowing for unique algorithm research.