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 …
Low-complexity acoustic scene classification for multi-device audio: Analysis of DCASE 2021 challenge systems
This paper presents the details of Task 1A Acoustic Scene Classification in the DCASE 2021
Challenge. The task targeted development of low-complexity solutions with good …
Challenge. The task targeted development of low-complexity solutions with good …
[PDF][PDF] CPJKU submission to dcase22: Distilling knowledge for lowcomplexity convolutional neural networks from a patchout audio transformer
In this technical report, we describe the CP-JKU team's submission for Task 1 Low-
Complexity Acoustic Scene Classification of the DCASE 22 challenge [1]. We use …
Complexity Acoustic Scene Classification of the DCASE 22 challenge [1]. We use …
[PDF][PDF] Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification.
Knowledge Distillation (KD) is known for its ability to compress large models into low-
complexity solutions while preserving high predictive performance. In Acoustic Scene …
complexity solutions while preserving high predictive performance. In Acoustic Scene …
[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 …
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 …
[PDF][PDF] CP-JKU submission to dcase23: Efficient acoustic scene classification with cp-mobile
In this technical report, we describe the CP-JKU team's submission for Task 1 Low-
Complexity Acoustic Scene Classification of the DCASE 23 challenge. We introduce a novel …
Complexity Acoustic Scene Classification of the DCASE 23 challenge. We introduce a novel …
A neural network-based howling detection method for real-time communication applications
Howling arises from acoustic coupling between the speaker and the microphone when it
creates positive feedback. Traditional public addressing systems and hearing aids devices …
creates positive feedback. Traditional public addressing systems and hearing aids devices …
An intelligent low-complexity computing interleaving wavelet scattering based mobile shuffling network for acoustic scene classification
XY Kek, CS Chin, Y Li - IEEE Access, 2022 - ieeexplore.ieee.org
The key towards a low complexity model for convolution neural network is in controlling the
number of parameters of the network and ensuring that the input representation is not …
number of parameters of the network and ensuring that the input representation is not …
Instance-level loss based multiple-instance learning framework for acoustic scene classification
WG Choi, JH Chang, JM Yang, HG Moon - Applied Acoustics, 2024 - Elsevier
An acoustic scene is inferred by detecting properties combining diverse sounds and
acoustic environments. This study is intended to discover these properties effectively using …
acoustic environments. This study is intended to discover these properties effectively using …