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Semi-Supervised Active Learning For Sound Classification In Hybrid Learning Environments

appsOther research productkeyboard_double_arrow_right Audiovisual 31 Aug 2016Publisher:Zenodo
Authors: Han Wenjing; Eduardo Coutinho; Ruan Huabin; Li Haifeng ; Bjorn Schuller; Yu Xiaojie; Zhu Xuan;

doi: 10.5281/zenodo.61295 , 10.5281/zenodo.61291

Semi-Supervised Active Learning For Sound Classification In Hybrid Learning Environments

Abstract

There are 16,930 sound instances in our database with durations ranging 242 from 1 to 10 seconds, which correspond to (approximately) 15 hours of environmental 243 sounds. All sound files were converted into raw 16 bit encoding, mono-channel, and 16 244 kHz sampling rate, as various formats and rates were used in the original versions 245 retrieved from the web.

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Keywords

Sound Classification, Active Learning, Semi-Supervised

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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