Data augmentation on convolutional neural networks to classify mechanical noise
Authors:
- Asith AbeysingheAAAsith Abeysinghe
- Sitthichart TohmuangSTSitthichart Tohmuang
- John Laurence DavyJDJohn Laurence Davy
- Mohammad FardMFMohammad Fard
- 9 January 2023
- journal article
- research article
- Published by Elsevier in Applied Acoustics
- Vol. 203
Abstract
No abstract availableKeywords
This publication has 27 references indexed in Scilit:
- Vocal effort compensation for MFCC feature extraction in a shouted versus normal speaker recognition taskComputer Speech & Language, 2019
- Audio Time Stretching Using Fuzzy Classification of Spectral BinsApplied Sciences, 2017
- ImageNet classification with deep convolutional neural networksCommunications of the ACM, 2017
- Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound ClassificationIEEE Signal Processing Letters, 2017
- MFCC-GMM based accent recognition system for Telugu speech signalsInternational Journal of Speech Technology, 2015
- Environmental sound classification with convolutional neural networks2015
- Data Augmentation for Deep Neural Network Acoustic ModelingIEEE/ACM Transactions on Audio, Speech, and Language Processing, 2015
- librosa: Audio and Music Signal Analysis in Python2015
- Vehicular Cabin Noise Source Identification and Optimization Using Beamforming and Acoustical HolographySAE International Journal of Advances and Current Practices in Mobility, 2014
- A novel approach for MFCC feature extraction2010