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Deep learning for high-level sound categorization

Patrice Guyot 1
Abstract : This document presents a short description of two systems for sound classification submitted at the data challenge Mak-ing Sense of Sounds in 2018. The aim of this challenge is to classify audio files into five different classes:Nature, Hu-man, Music, Effects, Urban, which were derived from human classification. For this challenge, the organizers provided a development dataset that consists of 1500 audio files of 5 second duration divided into the five categories, each containing300 files. The following parts describe the two submitted systems.The first system, called simplemind, consists of a Convolutional Neural Network (CNN). The second system, called nevermindis based on VGG-like model adapted from.
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https://hal.archives-ouvertes.fr/hal-02983149
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Submitted on : Monday, November 2, 2020 - 10:02:01 AM
Last modification on : Friday, August 27, 2021 - 11:26:03 AM
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  • HAL Id : hal-02983149, version 1

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Patrice Guyot. Deep learning for high-level sound categorization. 2018. ⟨hal-02983149⟩

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