Survey: Image mixing and deleting for data augmentation
Neural networks are prone to overfitting and memorizing data patterns. To avoid over-fitting
and enhance their generalization and performance, various methods have been suggested …
and enhance their generalization and performance, various methods have been suggested …
Byol for audio: Self-supervised learning for general-purpose audio representation
Inspired by the recent progress in self-supervised learning for computer vision that
generates supervision using data augmentations, we explore a new general-purpose audio …
generates supervision using data augmentations, we explore a new general-purpose audio …
Spectral images based environmental sound classification using CNN with meaningful data augmentation
In this study, an effective approach of spectral images based on environmental sound
classification using Convolutional Neural Networks (CNN) with meaningful data …
classification using Convolutional Neural Networks (CNN) with meaningful data …
Environmental sound classification using a regularized deep convolutional neural network with data augmentation
The adoption of the environmental sound classification (ESC) tasks increases very rapidly
over recent years due to its broad range of applications in our daily routine life. ESC is also …
over recent years due to its broad range of applications in our daily routine life. ESC is also …
Environment sound classification using a two-stream CNN based on decision-level fusion
With the popularity of using deep learning-based models in various categorization problems
and their proven robustness compared to conventional methods, a growing number of …
and their proven robustness compared to conventional methods, a growing number of …
Esresnet: Environmental sound classification based on visual domain models
Environmental Sound Classification (ESC) is an active research area in the audio domain
and has seen a lot of progress in the past years. However, many of the existing approaches …
and has seen a lot of progress in the past years. However, many of the existing approaches …
[HTML][HTML] Attention based convolutional recurrent neural network for environmental sound classification
Environmental sound classification (ESC) is a challenging problem due to the complexity of
sounds. The classification performance is heavily dependent on the effectiveness of …
sounds. The classification performance is heavily dependent on the effectiveness of …
Mixspeech: Data augmentation for low-resource automatic speech recognition
In this paper, we propose MixSpeech, a simple yet effective data augmentation method
based on mixup for automatic speech recognition (ASR). MixSpeech trains an ASR model …
based on mixup for automatic speech recognition (ASR). MixSpeech trains an ASR model …
A review of automated bioacoustics and general acoustics classification research
Automated bioacoustics classification has received increasing attention from the research
community in recent years due its cross-disciplinary nature and its diverse application …
community in recent years due its cross-disciplinary nature and its diverse application …
Environment sound classification using multiple feature channels and attention based deep convolutional neural network
In this paper, we propose a model for the Environment Sound Classification Task (ESC) that
consists of multiple feature channels given as input to a Deep Convolutional Neural Network …
consists of multiple feature channels given as input to a Deep Convolutional Neural Network …