Difference between revisions of "2009:Audio Onset Detection Results"

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===MIREX 2009 Audio Onset Detection Runtime Data===
 
===MIREX 2009 Audio Onset Detection Runtime Data===
 
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<csv>onset/onset.runtime.csv</csv>
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==Results by Class==
 
==Results by Class==

Revision as of 13:52, 15 October 2009

Introduction

These are the results for the 2009 running of the Audio Onset Detection. For background information about this task set please refer to the Audio_Onset_detection page. The aim of the Audio Onset Detection task is to find the time locations at which all musical events in a recording begin. The dataset consists of 85 recordings across 9 different "classes" (e.g. solo drums, polyphonic pitched, etc.). For each sound file, ground truth annotations produced by 3-5 listeners were used for the evaluation.

General Legend

Team ID

AR1 = A. R├╢bel (7_hd)
AR2 = A. R├╢bel (10_hd)
AR3 = A. R├╢bel (12_nhd)
AR4 = A. R├╢bel (16_nhd)
AR5 = A. R├╢bel (19_hdc)
GT = George Tzanetakis
PI = Antonio Pertusa, José M. Iñesta
TZC1 = Hui Li Tan, Yongwei Zhu, Lekha Chaisorn
TZC2 = Hui Li Tan, Yongwei Zhu, Lekha Chaisorn
TZC3 = Hui Li Tan, Yongwei Zhu, Lekha Chaisorn
TZC4 = Hui Li Tan, Yongwei Zhu, Lekha Chaisorn
TZC5 = Hui Li Tan, Yongwei Zhu, Lekha Chaisorn

Overall Summary Results

MIREX 2009 Audio Onset Detection Summary Results - Peak F-measure performance across all parameterizations

file /nema-raid/www/mirex/results/onset/onset.total.csv not found

MIREX 2009 Audio Onset Detection Runtime Data

file /nema-raid/www/mirex/results/onset/onset.runtime.csv not found

Results by Class

Individual Results