End-to-End Environmental Sound Classification using a 1D Convolutional Neural Network

Published in

Expert systems with applications(2019)

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TL;DR

An end-to-end approach for environmental sound classification based on a 1D Convolution Neural Network that learns a representation directly from the audio signal that outperforms most of the state-of-the-art approaches that use handcrafted features or 2D representations as input.

Authors

Alessandro Lameiras Koerich

2 papers

P. Cardinal

2 papers

Sajjad Abdoli

1 papers

References54 items

Investigation of acoustic and visual features for acoustic scene classification

A Robust Approach for Securing Audio Classification Against Adversarial Attacks

Segmentation and characterization of acoustic event spectrograms using singular value decomposition

Environment Sound Classification Using a Two-Stream CNN Based on Decision-Level Fusion

Speaker Recognition from Raw Waveform with SincNet

End-to-End Environmental Sound Classification using a 1D Convolutional Neural Network

Published in

Expert systems with applications(2019)

External Links:

Generate Graph DownloadPDF

TL;DR

Authors

Alessandro Lameiras Koerich

2 papers

P. Cardinal

2 papers

Sajjad Abdoli

1 papers

References54 items

Investigation of acoustic and visual features for acoustic scene classification

A Robust Approach for Securing Audio Classification Against Adversarial Attacks

Segmentation and characterization of acoustic event spectrograms using singular value decomposition

Environment Sound Classification Using a Two-Stream CNN Based on Decision-Level Fusion

Speaker Recognition from Raw Waveform with SincNet

An Ensemble Stacked Convolutional Neural Network Model for Environmental Event Sound Recognition

End-to-End Speech Recognition From the Raw Waveform

Randomly Weighted CNNs for (Music) Audio Classification

Learning from Between-class Examples for Deep Sound Recognition

Sample-Level CNN Architectures for Music Auto-Tagging Using Raw Waveforms

Squeeze-and-Excitation Networks

Learning environmental sounds with end-to-end convolutional neural network

An evaluation of Convolutional Neural Networks for music classification using spectrograms

SoundNet: Learning Sound Representations from Unlabeled Video

Very deep convolutional neural networks for raw waveforms

CNN architectures for large-scale audio classification

Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification

Automatic Environmental Sound Recognition: Performance Versus Computational Cost

The Implementation of Low-cost Urban Acoustic Monitoring Devices

Learning Multiscale Features Directly from Waveforms

Acoustic scene classification with matrix factorization for unsupervised feature learning

Acoustic Event Classification using spectral band selection and Non-Negative Matrix Factorization-based features

Detection of overlapping acoustic events using a temporally-constrained probabilistic model

Improving event detection for audio surveillance using Gabor filterbank features

Deep Residual Learning for Image Recognition

Environmental sound classification with convolutional neural networks

ESC: Dataset for Environmental Sound Classification

Detection and Classification of Acoustic Scenes and Events

Speech acoustic modeling from raw multichannel waveforms

Sound event detection in real life recordings using coupled matrix factorization of spectral representations and class activity annotations

Unsupervised feature learning for urban sound classification

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

A Dataset and Taxonomy for Urban Sound Research

Very Deep Convolutional Networks for Large-Scale Image Recognition

Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning

End-to-end learning for music audio

ADADELTA: An Adaptive Learning Rate Method

Music genre classification using LBP textural features

Environmental Sound Recognition With Time–Frequency Audio Features

Audio analysis for surveillance applications

On Combining Classifiers

DARPA TIMIT:: acoustic-phonetic continuous speech corpus CD-ROM, NIST speech disc 1-1.1

Classifying environmental sounds using image recognition networks

A Software Framework for Musical Data Augmentation

Learning the speech front-end with raw waveform CLDNNs

Acoustic Scene Classification

Dropout: a simple way to prevent neural networks from overfitting

Gammatone-like spectrograms, web resource.

The Physics and Psychophysics of Music: An Introduction

The Physics and Psychophysics of Music

Calculation of a constant Q spectral transform

Expert Systems With Applications

Unsupervised feature learning 532 for environmental sound classification using cycle consistent generative adversarial 533 network

Field of Study

Computer ScienceMathematics

Journal Information

Name

ArXiv

Volume

abs/2005.00687

Venue Information

Name

Expert systems with applications

Type

journal

URL

https://www.journals.elsevier.com/expert-systems-with-applications/

Alternate Names

Expert syst appl
Expert Systems With Applications
Expert Syst Appl

TL;DR

Authors

References54 items

Investigation of acoustic and visual features for acoustic scene classification

A Robust Approach for Securing Audio Classification Against Adversarial Attacks

Segmentation and characterization of acoustic event spectrograms using singular value decomposition

Environment Sound Classification Using a Two-Stream CNN Based on Decision-Level Fusion

Speaker Recognition from Raw Waveform with SincNet

TL;DR

Authors

References54 items

Investigation of acoustic and visual features for acoustic scene classification

A Robust Approach for Securing Audio Classification Against Adversarial Attacks

Segmentation and characterization of acoustic event spectrograms using singular value decomposition

Environment Sound Classification Using a Two-Stream CNN Based on Decision-Level Fusion

Speaker Recognition from Raw Waveform with SincNet

An Ensemble Stacked Convolutional Neural Network Model for Environmental Event Sound Recognition

End-to-End Speech Recognition From the Raw Waveform

Randomly Weighted CNNs for (Music) Audio Classification

Learning from Between-class Examples for Deep Sound Recognition

Sample-Level CNN Architectures for Music Auto-Tagging Using Raw Waveforms

Squeeze-and-Excitation Networks

Learning environmental sounds with end-to-end convolutional neural network

An evaluation of Convolutional Neural Networks for music classification using spectrograms

SoundNet: Learning Sound Representations from Unlabeled Video

Very deep convolutional neural networks for raw waveforms

CNN architectures for large-scale audio classification

Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification

Automatic Environmental Sound Recognition: Performance Versus Computational Cost

The Implementation of Low-cost Urban Acoustic Monitoring Devices

Learning Multiscale Features Directly from Waveforms

Acoustic scene classification with matrix factorization for unsupervised feature learning

Acoustic Event Classification using spectral band selection and Non-Negative Matrix Factorization-based features

Detection of overlapping acoustic events using a temporally-constrained probabilistic model

Improving event detection for audio surveillance using Gabor filterbank features

Deep Residual Learning for Image Recognition

Environmental sound classification with convolutional neural networks

ESC: Dataset for Environmental Sound Classification

Detection and Classification of Acoustic Scenes and Events

Speech acoustic modeling from raw multichannel waveforms

Sound event detection in real life recordings using coupled matrix factorization of spectral representations and class activity annotations

Unsupervised feature learning for urban sound classification

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

A Dataset and Taxonomy for Urban Sound Research

Very Deep Convolutional Networks for Large-Scale Image Recognition

Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning

End-to-end learning for music audio

ADADELTA: An Adaptive Learning Rate Method

Music genre classification using LBP textural features

Environmental Sound Recognition With Time–Frequency Audio Features

Audio analysis for surveillance applications

On Combining Classifiers

DARPA TIMIT:: acoustic-phonetic continuous speech corpus CD-ROM, NIST speech disc 1-1.1

Classifying environmental sounds using image recognition networks

A Software Framework for Musical Data Augmentation

Learning the speech front-end with raw waveform CLDNNs

Deep Learning

Acoustic Scene Classification

Dropout: a simple way to prevent neural networks from overfitting

Gammatone-like spectrograms, web resource.

The Physics and Psychophysics of Music: An Introduction

The Physics and Psychophysics of Music

Calculation of a constant Q spectral transform

Expert Systems With Applications

Unsupervised feature learning 532 for environmental sound classification using cycle consistent generative adversarial 533 network

Field of Study

Journal Information

Name

Volume

Venue Information

Name

Type

URL

Alternate Names