2005:Audio Onset Detect
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.
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:
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.
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.
