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 …
A survey on preprocessing and classification techniques for acoustic scene
There are lots of research papers for ASC, and in recent years it is rapidly increasing.
DCASE also provides different types of competition for the submission of several papers to …
DCASE also provides different types of competition for the submission of several papers to …
Acoustic scene classification in dcase 2020 challenge: generalization across devices and low complexity solutions
This paper presents the details of Task 1: Acoustic Scene Classification in the DCASE 2020
Challenge. The task consists of two subtasks: classification of data from multiple devices …
Challenge. The task consists of two subtasks: classification of data from multiple devices …
Receptive field regularization techniques for audio classification and tagging with deep convolutional neural networks
K Koutini, H Eghbal-zadeh… - IEEE/ACM Transactions …, 2021 - ieeexplore.ieee.org
In this paper, we study the performance of variants of well-known Convolutional Neural
Network (CNN) architectures on different audio tasks. We show that tuning the Receptive …
Network (CNN) architectures on different audio tasks. We show that tuning the Receptive …
Stavis: Spatio-temporal audiovisual saliency network
We introduce STAViS, a spatio-temporal audiovisual saliency network that combines spatio-
temporal visual and auditory information in order to efficiently address the problem of …
temporal visual and auditory information in order to efficiently address the problem of …
[PDF][PDF] CP-JKU submissions to DCASE'20: Low-complexity cross-device acoustic scene classification with rf-regularized CNNs
This technical report describes the CP-JKU team's submission for Task 1–Subtask A
(Acoustic Scene Classification with Multiple Devices) and Subtask B (Low-Complexity …
(Acoustic Scene Classification with Multiple Devices) and Subtask B (Low-Complexity …
CAA-Net: Conditional atrous CNNs with attention for explainable device-robust acoustic scene classification
Acoustic Scene Classification (ASC) aims to classify the environment in which the audio
signals are recorded. Recently, Convolutional Neural Networks (CNNs) have been …
signals are recorded. Recently, Convolutional Neural Networks (CNNs) have been …
[PDF][PDF] Distilling the knowledge of transformers and CNNs with CP-mobile
Designing lightweight models that require limited computational resources and can operate
on edge devices is a major trajectory in deep learning research. In the context of Acoustic …
on edge devices is a major trajectory in deep learning research. In the context of Acoustic …
Device-robust acoustic scene classification via impulse response augmentation
The ability to generalize to a wide range of recording devices is a crucial performance factor
for audio classification models. The characteristics of different types of microphones …
for audio classification models. The characteristics of different types of microphones …
RQNet: Residual quaternion CNN for performance enhancement in low complexity and device robust acoustic scene classification
Acoustic Scene Classification aims to recognize the unique acoustic characteristics of an
environment. Recently, Convolutional Neural Networks (CNNs) have boosted the accuracy …
environment. Recently, Convolutional Neural Networks (CNNs) have boosted the accuracy …