IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events

http://www.elec.qmul.ac.uk/digitalmusic/sceneseventschallenge/

Proposal Document: http://www.elec.qmul.ac.uk/digitalmusic/sceneseventschallenge/AASP_CASA.pdf

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Development Dataset for Event Detection Task, subtask 2 - OS

Dataset developers: Mathias Rossignol, Mathieu Lagrange, Dimitrios Giannoulis, Emmanouil Benetos, Dan Stowell, and Mark Plumbley

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The development dataset for the OS subtask consists of 1 file:

* events_OS_development.zip

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The development dataset contains mono recordings (.wav) containing artificially concatenated overlapped acoustic events in an office environment. There are 3 SNRs of events over background noise (+6, 0, and -6 dB) and 3 levels of "density" of events (low, medium, and high). In this dataset, all events have the same probability and SNR. The dataset contains events from 16 different classes, which are as follows:

* alert (short alert sound)
* clearthroat (clearing throat)
* cough
* doorslam (door slam)
* drawer
* keyboard (keyboard clicks)
* keys (keys put on table)
* knock (door knock)
* laughter
* mouse (mouse click)
* pageturn (page turning)
* pendrop (pen, pencil, or marker touching table surfaces)
* phone
* printer
* speech
* switch

Filenames are as follows: 'office_snrX_Y.wav', where X={0,6,-6} denotes the SNR and Y={low,med,high} denotes the event density. 

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Each .wav recording is accompanied by an annotation file (.txt format). Each .txt file contains information about the onset, offset, and event class for each event present in the recording, and is structured as follows:

onset1	offset1	EventID1
onset2	offset2	EventID2
...

where 'onset' refers to the onset time in seconds, 'offset' refers to the offset time in seconds, and EventID is a string corresponding to the event class as shown in the list above. The three values are separated by tabs.

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Also included for each recording is a piano-roll representation in .png format of the events present.

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For any problems with this dataset, please contact: aasp-challenge-owner@eecs.qmul.ac.uk