Title: MAESTRO Synthetic - Multiple Annotator Estimated STROng labels
Machine Listening Group, Tampere University https://research.tuni.fi/machinelistening/
MAESTRO synthetic contains 20 synthetic audio files created using Scaper, each of them 3 minutes long. The dataset was created for studying annotation procedures for strong labels using crowdsourcing.
The audio files contain sounds from the following classes:
Audio files contain excerpts of recordings uploaded to freesound.org. Please see FREESOUNDCREDITS.txt for an attribution list.
Audio files are generated using Scaper, with small changes to the synthesis procedure: Sounds were placed at random intervals, controlling for a maximum polyphony of 2. Intervals between two consecutive events are selected at random, but limited to 2-10 seconds. Event classes and event instances are chosen uniformly, and mixed with a signal-to-noise ratio (SNR) randomly selected between 0 and 20 dB over a Brownian noise background. Having two overlapping events from the same class is avoided.
For annotation, each file of 3 minutes was split into 10-second segments, with a hop of one second. Each segment was annotated using crowdsourcing, in a tagging scenario.
For each segment, the annotators were required to select from the given list of classes the sounds active (audible). Each 10-s segment was annotated by five persons.
Full details on the annotation procedure and the processing of the tags can be found in:
Irene Martin Morato, Manu Harju, and Annamaria Mesaros. Crowdsourcing strong labels for sound event detection, in IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA 2021). New Paltz, NY, Oct 2021.
The dataset contains:
Each 3-minute file was split into 10-s segments with a 1-s hop. For example, scape_00.wav contains the segments 000000.wav - 000170.wav. The correspondence between them is as follows: 000000.wav starts at offset 0, 000001.wav starts at offset 1 s, 000002.wav starts at offset 2 s, etc
dataset root │ README.md this file │ FREESOUNDCREDITS.txt information on the individual sound examples used in the data │ files_mapping.csv mapping between freesound id and sound instances extracted from them, format file.wav [tab] label [tab] saliency [tab] freesound_id [tab] start_time [tab] end_time │ └───audio │ │ scape00.wav │ │ scape01.wav │ │ ... │ └───estimated_strong_labels outcome of the method (using MACE) │ │ mturk_scape00.csv format: start_time [tab] end_time [tab] label │ │ mturk_scape01.csv │ │ ... │ └───scaper_reference ground truth created with Scaper (annotations, output from Scaper) │ │ scape00.jams │ │ scape00.txt │ │ scape01.jams │ │ scape01.txt │ │ ... └───tags │ │ MAESTRO_full_annotations.yaml complete multi-annotator tags for all 10-s segments │ │ MAESTRO_labels_mace100.csv aggregated tags per segment, based on multiple annotations(using MACE); format: filename [tab]tag1,tag2,..
License permits free academic usage. Any commercial use is strictly prohibited. For commercial use, contact dataset authors.
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