MATS - Multi-Annotator Tagged Soundscapes

This is a dataset containing <strong>audio tags</strong> 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. <em>What is the ground truth? Reliability of multi-annotator data for audio tagging, </em>29th European Signal Processing Conference, EUSIPCO 2021 The dataset contains the following: <strong>raw annotations</strong> provided by 133 annotators, multiple opinions per audio file <strong> </strong>MATS_labels_full_annotations.yaml<em> </em> content formatted as: - filename: file1.wav <br> annotations:<br> - annotator_id: ann_1<br> tags:<br> - tag1<br> - tag2<br> - annotator_id: ann_3<br> tags:<br> - tag1<br> - filename: file3.wav <br> ... <strong>processed annotations</strong> using different methods, as presented in the accompanying paper MATS_labels_majority_vote.csv<br> MATS_labels_union.csv<br> MATS_labels_mace100.csv <br> MATS_labels_mace100_competence60 content formatted as: filename [tab] tag1,tag2,tag3 <br> The audio files can be downloaded from https://zenodo.org/record/2589280 and are covered by their own license.