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DCASE 2017 Challenge setup: Tasks, datasets and baseline system

Annamaria Mesaros 1 Toni Heittola 1 Aleksandr Diment 1 Benjamin Elizalde 2 Ankit Shah 2 Emmanuel Vincent 3 Bhiksha Raj 2 Tuomas Virtanen 1
1 TUT - Tampere University of Technology [Tampere]
2 Computer Science Department - Carnegie Mellon University
3 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : DCASE 2017 Challenge consists of four tasks: acoustic scene classification , detection of rare sound events, sound event detection in real-life audio, and large-scale weakly supervised sound event detection for smart cars. This paper presents the setup of these tasks: task definition, dataset, experimental setup, and baseline system results on the development dataset. The baseline systems for all tasks rely on the same implementation using multilayer perceptron and log mel-energies, but differ in the structure of the output layer and the decision making process, as well as the evaluation of system output using task specific metrics.
Keywords : Sound scene analysis Acoustic scene classification Sound event detection Audio tagging Rare sound events Weak labels
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https://hal.inria.fr/hal-01627981
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Submitted on : Thursday, November 2, 2017 - 4:45:25 PM
Last modification on : Thursday, August 22, 2019 - 12:10:38 PM
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Annamaria Mesaros, Toni Heittola, Aleksandr Diment, Benjamin Elizalde, Ankit Shah, et al.. DCASE 2017 Challenge setup: Tasks, datasets and baseline system. DCASE 2017 - Workshop on Detection and Classification of Acoustic Scenes and Events, Nov 2017, Munich, Germany. ⟨hal-01627981⟩

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