MATS - Multi-Annotator Tagged Soundscapes

Dataset

Description

This is a dataset containing audio tags for a number of 3930 audio files of the TAU Urban Acoustic Scenes 2019 development dataset (airport, public square, and park). The files were annotated using a web-based tool, with multiple annotators providing labels for each file. The dataset contains annotations for 3930 files, annotated with the following tags: announcement jingle announcement speech adults talking birds singing children voices dog barking footsteps music siren traffic noise The annotation procedure and processing is presented in the paper: Irene Martin-Morato, Annamaria Mesaros. What is the ground truth? Reliability of multi-annotator data for audio tagging, 29th European Signal Processing Conference, EUSIPCO 2021 The dataset contains the following: raw annotations provided by 133 annotators, multiple opinions per audio file MATS_labels_full_annotations.yaml content formatted as: - filename: file1.wav annotations: - annotator_id: ann_1 tags: - tag1 - tag2 - annotator_id: ann_3 tags: - tag1 - filename: file3.wav ... processed annotations using different methods, as presented in the accompanying paper MATS_labels_majority_vote.csv MATS_labels_union.csv MATS_labels_mace100.csv MATS_labels_mace100_competence60 content formatted as: filename [tab] tag1,tag2,tag3 The audio files can be downloaded from https://zenodo.org/record/2589280 and are covered by their own license.
Date made available21 May 2021
PublisherZenodo

Field of science, Statistics Finland

  • 113 Computer and information sciences
  • What is the ground truth? Reliability of multi-annotator data for audio tagging

    Martin Morato, I. & Mesaros, A., 2021, 29th European Signal Processing Conference EUSIPCO 2021. IEEE, 5 p. 1173

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    File
    33 Citations (Scopus)
    15 Downloads (Pure)

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