DCASE 2022 Task 5: Few-shot Bioacoustic Event Detection Development Set
Zenodo (CERN European Organization for Nuclear Research)
Abstract
General Description: The development set for task 5 of DCASE 2022 "Few-shot Bioacoustic Event Detection" consists of 192 audio files acquired from different bioacoustic sources. The dataset is split into training and validation sets. Multi-class annotations are provided for the training set with positive (POS), negative (NEG) and unkwown (UNK) values for each class. UNK indicates uncertainty about a class. Single-class (class of interest) annotations are provided for the validation set, with events marked as positive (POS) or unkwown (UNK) provided for the class of interest. this version (3): * fixes issues with annotations from HB set Folder Structure: Development_Set.zip |_Development_Set/ |__Training_Set/ |___JD/ |____*.wav |____*.csv |___HT/ |____*.wav |____*.csv |___BV/ |____*.wav |____*.csv |___MT/ |____*.wav |____*.csv |___WMW/ |____*.wav |____*.csv |__Validation_Set/ |___HB/ |____*.wav |____*.csv |___PB/ |____*.wav |____*.csv |___ME/ |____*.wav |____*.csv Development_Set_Annotations.zip has the same structure but contains only the *.csv files ## Dataset statistics Some statistics on this dataset are as follows, split between training and validation set and their sub-folders: ----------------------------------------------------- TRAINING SET ----------------------------------------------------- Number of audio recordings | 174 Total duration | 21 hours Total classes | 47 Total events | 14229 ----------------------------------------------------- TRAINING SET/BV ----------------------------------------------------- Number of audio recordings | 5 Total duration | 10 hours Total classes | 11 Total events | 9026 Ratio event/duration | 0.04 Sampling rate | 24000 Hz ----------------------------------------------------- TRAINING SET/HT ----------------------------------------------------- Number of audio recordings | 5 Total duration | 5 hours Total classes | 5 Total events | 611 Ratio event/duration | 0.05 Sampling rate | 6000 Hz ----------------------------------------------------- TRAINING SET/JD ----------------------------------------------------- Number of audio recordings | 1 Total duration | 10 mins Total classes | 1 Total events | 357 Ratio event/duration | 0.06 Sampling rate | 22050 Hz ----------------------------------------------------- TRAINING SET/MT ----------------------------------------------------- Number of audio recordings | 2 Total duration | 1 hour and 10 mins Total classes | 4 Total events | 1294 Ratio event/duration | 0.04 Sampling rate | 8000 Hz ----------------------------------------------------- TRAINING SET/WMW ----------------------------------------------------- Number of audio recordings | 161 Total duration | 4 hours and 40 mins Total classes | 26 Total events | 2941 Ratio event/duration | 0.24 Sampling rate | various sampling rates ----------------------------------------------------- ----------------------------------------------------- VALIDATION SET ----------------------------------------------------- Number of audio recordings | 18 Total duration | 5 hours and 57 minutes Total classes | 5 Total events | 1077 ----------------------------------------------------- VALIDATION SET/HB ----------------------------------------------------- Number of audio recordings | 10 Total duration | 2 hours and 38 minutes Total classes | 1 Total events | 712 Ratio event/duration | 0.7 Sampling rate | 44100 Hz ----------------------------------------------------- VALIDATION SET/PB ----------------------------------------------------- Number of audio recordings | 6 Total duration | 3 hours Total classes | 2 Total events | 292 Ratio event/duration | 0.003 Sampling rate | 44100 Hz ----------------------------------------------------- VALIDATION SET/ME ----------------------------------------------------- Number of audio recordings | 2 Total duration | 20 minutes Total classes | 2 Total events | 73 Ratio event/duration | 0.01 Sampling rate | 44100 Hz ----------------------------------------------------- Annotation structure Each line of the annotation csv represents an event in the audio file. The column descriptions are as follows: TRAINING SET --------------------- Audiofilename, Starttime, Endtime, CLASS_1, CLASS_2, ...CLASS_N VALIDATION SET --------------------- Audiofilename, Starttime, Endtime, Q Classes DCASE2022_task5_training_set_classes.csv and DCASE2022_task5_validation_set_classes.csv provide a table with class code correspondence to class name for all classes in the Development set. DCASE2022_task5_training_set_classes.csv --------------------- dataset, class_code, class_name DCASE2022_task5_validation_set_classes.csv --------------------- dataset, recording, class_code, class_name Evaluation Set The Evaluation set for this task will be released on the 1st of June 2022 Open Access: This dataset is available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. Contact info: Please send any feedback or questions to: Ines Nolasco - i.dealmeidanolasco@qmul.ac.uk
Authors 14
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Queen Mary University of London
Affiliation as printed
Queen Mary University of London (QMUL)
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Queen Mary University of London
Affiliation as printed
Queen Mary University of London (QMUL)
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University of Konstanz · Max Planck Institute of Animal Behavior
Affiliation as printed
University of Konstanz & Max Planck Institute of Animal Behavior
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Affiliation as printed
Biotopia, Naturkundemuseum Bayern
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Affiliation as printed
AGH University of Science and Technology,
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Affiliation as printed
University of Oxford
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Queen Mary University of London
Affiliation as printed
Queen Mary University of London (QMUL)
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Affiliation as printed
Syracuse University
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Affiliation as printed
University of Salford
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Affiliation as printed
University of Surrey
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Affiliation as printed
La Salle, Universitat Ramon Llull
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Centre National de la Recherche Scientifique
Affiliation as printed
Centre National de la Recherche Scientifique (CNRS)
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Queen Mary University of London
Affiliation as printed
Queen Mary University of London (QMUL)
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Dan Stowell Aachen
Naturalis Biodiversity Center · Tilburg University
Affiliation as printed
Tilburg University & Naturalis Biodiversity Centre
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