research data . Dataset . Under curation

MAESTRO Synthetic - Multi-Annotator Estimated Strong Labels

Irene Martin Morato; Manu Harju; Annamaria Mesaros;
Open Access
  • Publisher: Zenodo
Abstract
The dataset was created for studying estimation of strong labels using crowdsourcing. It contains 20 synthetic audio files created using Scaper, the reference annotation created with Scaper, and the annotation outcome. Annotation was performed using Amazon Mechanical Turk. Audio files contain excerpts of recordings uploaded to freesound.org.(from Urban Sound 8k dataset). Please see FREESOUNDCREDITS.txt for an attribution list. The dataset contains: audio: the 20 synthetic soundscapes, each 3 min long ground truth: the "true" reference annotation created using Scaper estimated strong labels: the reference annotation created from the crowdsour...
Persistent Identifiers
Funded by
AKA| Teaching machines to listen
Project
  • Funder: Academy of Finland (AKA)
  • Project Code: 332063
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