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

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

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 rate...

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Bibliographische Detailangaben
Hauptverfasser: Wenjing, Han, Coutinho, Eduardo, Huabin, Ruan, Haifeng, Li, Bj Orn Schuller, Xiaojie, Yu, Xuan, Zhu
Format: Video
Sprache:eng
Schlagworte:
Active Learning
Sound Classification
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Beschreibung
Zusammenfassung: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.
DOI:10.5281/zenodo.61291