Acoustic scene classification: a comprehensive survey
Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …
applications. Various audio signal processing and machine learning methods have been …
Rethinking CNN models for audio classification
In this paper, we show that ImageNet-Pretrained standard deep CNN models can be used
as strong baseline networks for audio classification. Even though there is a significant …
as strong baseline networks for audio classification. Even though there is a significant …
Comparison of pre-trained CNNs for audio classification using transfer learning
The paper investigates retraining options and the performance of pre-trained Convolutional
Neural Networks (CNNs) for sound classification. CNNs were initially designed for image …
Neural Networks (CNNs) for sound classification. CNNs were initially designed for image …
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 …
Masked spectrogram prediction for self-supervised audio pre-training
Transformer-based models attain excellent results and generalize well when trained on
sufficient amounts of data. However, constrained by the limited data available in the audio …
sufficient amounts of data. However, constrained by the limited data available in the audio …
Specaugment++: A hidden space data augmentation method for acoustic scene classification
In this paper, we present SpecAugment++, a novel data augmentation method for deep
neural networks based acoustic scene classification (ASC). Different from other popular data …
neural networks based acoustic scene classification (ASC). Different from other popular data …
Environment sound classification using an attention-based residual neural network
AM Tripathi, A Mishra - Neurocomputing, 2021 - Elsevier
Complexity of environmental sounds impose numerous challenges for their classification.
The performance of Environmental Sound Classification (ESC) depends greatly on how …
The performance of Environmental Sound Classification (ESC) depends greatly on how …
Improving the performance of automated audio captioning via integrating the acoustic and semantic information
Automated audio captioning (AAC) has developed rapidly in recent years, involving acoustic
signal processing and natural language processing to generate human-readable sentences …
signal processing and natural language processing to generate human-readable sentences …
A deep learning approach for detecting drill bit failures from a small sound dataset
Monitoring the conditions of machines is vital in the manufacturing industry. Early detection
of faulty components in machines for stopping and repairing the failed components can …
of faulty components in machines for stopping and repairing the failed components can …
Attentional graph convolutional network for structure-aware audiovisual scene classification
Audiovisual scene understanding is a challenging problem due to the unstructured spatial–
temporal relations that exist in the audio signals and spatial layouts of different objects in the …
temporal relations that exist in the audio signals and spatial layouts of different objects in the …