Difference between revisions of "2005:Audio Onset Detect"

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==Description==
 
  
The aim of this contest is to compare state-of-the-art onset detection algorithms on music recordings. The methods will be evaluated on a large, various and reliably-annotated dataset, composed of sub-datasets grouping files of the same type.
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1) '''Input data'''
 
  
''Audio format'':
 
  
The data are monophonic sound files, with the associated onset times and
 
data about the annotation robustness.
 
* CD-quality (PCM, 16-bit, 44100 Hz)
 
* single channel (mono)
 
* file length between 2 and 36 seconds (total time: 14 minutes)
 
* File names:
 
  
''Audio content'':
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The dataset is subdivided into classes, because onset detection is sometimes performed in applications dedicated to a single type of signal (ex: segmentation of a single track in a mix, drum transcription, complex mixes databases segmentation...). The performance of each algorithm will be assessed on the whole dataset but also on each class separately.
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The dataset contains 85 files from 5 classes annotated as follows:
 
* 30 solo drum excerpts cross-annotated by 3 people
 
* 30 solo monophonic pitched instruments excerpts cross-annotated by 3 people
 
* 10 solo polyphonic pitched instruments excerpts cross-annotated by 3 people
 
* 15 complex mixes cross-annotated by 5 people
 
 
 
Moreover the monophonic pitched instruments class is divided into 6 sub-classes: brass (2 excerpts), winds (4), sustained strings (6), plucked strings (9), bars and bells (4), singing voice (5).
 
 
 
''Nomenclature''
 
 
 
<AudioFileName>.wav for the audio file
 
 
 
 
 
2) '''Output data'''
 
 
 
The onset detection algoritms will return onset times in a text file: <Results of evaluated Algo path>/<AudioFileName>.output.
 
 
 
 
 
''Onset file Format''
 
 
 
<onset time(in seconds)>\n
 
 
 
where \n denotes the end of line. The < and > characters are not included.
 

Revision as of 17:42, 21 September 2005