Sep 26, 2016 · In this paper, we propose a unified acoustic recognition framework taking advantage of primitive feature input without injuring discriminant ...
Efficient Feature Extraction 100% · Sound Scene 50% · Acoustic Recognition 50% · Audio Recognition 50% · Discriminant Information 50% · Subspace Representation 50% ...
Download Citation | On Aug 1, 2016, Xiaoyan Wang and others published Large Scale Environmental Sound Classification Based on Efficient Feature Extraction ...
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Apr 22, 2022 · This paper proposes a resource adaptive convolutional neural network (RACNN). RACNN uses a novel resource adaptive convolutional (RAC) module.
An improved compact bilinear attention network (ICBA-Net) is proposed to more precisely focus on the regions that need attention in feature maps in this paper.
A descriptive survey for Environmental sound classification (ESC) detailing datasets, preprocessing techniques, features and classifiers is done.
Nov 8, 2022 · Urban sound classification presents unstructured characteristics filled with noise and sounds unrelated to the sound event under study.
This paper reports our study on employing various acoustic features aggregation and data enhancement approaches for the effective classification of ...
The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification.
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