DASED: A Multi-Domain Dataset for Sound Event Detection Domain Adaptation

Oct 19, 2018 NIPS 2018 Workshop IRASL Blind Submission readers: everyone
  • Abstract: In this paper we present the first freely available dataset for the development and evaluation of domain adaptation methods, for the sound event detection task. The dataset contains 40 log mel-band energies extracted from $100$ different synthetic sound event tracks, with additive noise from nine different acoustic scenes (from indoor, outdoor, and vehicle environments), mixed at six different sound-to-noise ratios, SNRs, (from -12 to -27 dB with a step of -3 dB), and totaling to 5400 (9 * 100 * 6) sound files and a total length of 30 564 minutes. We provide the dataset as is, the code to re-create the dataset and remix the sound event tracks and the acoustic scenes with different SNRs, and a baseline method that tests the adaptation performance with the proposed dataset and establishes some first results.
  • TL;DR: The very first freely available domain adaptation dataset for sound event detection.
  • Keywords: Domain adaptation, sound event detection, dataset
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