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ESC: Dataset for Environmental Sound Classification

Piczak, Karol J.·2015·Proceedings of the 23rd ACM international conference on Multimedia

Abstract

One of the obstacles in research activities concentrating on environmental sound classification is the scarcity of suitable and publicly available datasets. This paper tries to address that issue by presenting a new annotated collection of 2000 short clips comprising 50 classes of various common sound events, and an abundant unified compilation of 250000 unlabeled auditory excerpts extracted from recordings available through the Freesound project. The paper also provides an evaluation of human accuracy in classifying environmental sounds and compares it to the performance of selected baseline classifiers using features derived from mel-frequency cepstral coefficients and zero-crossing rate.

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Metadata

Authors
Piczak, K. J.
Venue
Proceedings of the 23rd ACM international conference on Multimedia
Publisher
ACM
Published
2015-10-13
Pages
1015-1018
OpenAlex
W2052666245
Cited by
1,397
References
0
FWCI
17.69
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: ESC: Dataset for Environmental Sound Classification. https://app.cochat.ai/papers/10.1145/2733373.2806390
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Piczak, K. J. (2015). ESC: Dataset for Environmental Sound Classification. Proceedings of the 23rd ACM international conference on Multimedia. https://doi.org/10.1145/2733373.2806390

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