Performance analysis of multiple aggregated acoustic features for environment sound classification
Authors:
- Yu SuYSYu Su
- Ke ZhangKZKe Zhang
- Jingyu WangJWJingyu Wang
- Daming ZhouDZDaming Zhou
- Kurosh MadaniKMKurosh Madani
- 1 January 2020
- journal article
- research article
- Published by Elsevier in Applied Acoustics
- Vol. 158
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China
- Shaanxi Provincial Science and Technology Department
This publication has 15 references indexed in Scilit:
- Double mode surveillance system based on remote audio/video signals acquisitionApplied Acoustics, 2018
- Toward identifying crack-length-related resonances in acoustic emission waveforms for structural health monitoring applicationsStructural Health Monitoring, 2017
- Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound ClassificationIEEE Signal Processing Letters, 2017
- ESC2015
- Robust sound event recognition using convolutional neural networks2015
- Environmental sound recognition: a surveyAPSIPA Transactions on Signal and Information Processing, 2014
- Psychology of auditory perceptionWIREs Cognitive Science, 2010
- Audio thumbnailing of popular music using chroma-based representationsIEEE Transactions on Multimedia, 2005
- Introduction to Neo-Riemannian Theory: A Survey and a Historical PerspectiveJournal of Music Theory, 1998
- Derivation of auditory filter shapes from notched-noise dataHearing Research, 1990