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 …
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 …
Anomalous sound detection as a simple binary classification problem with careful selection of proxy outlier examples
P Primus, V Haunschmid, P Praher… - arXiv preprint arXiv …, 2020 - arxiv.org
Unsupervised anomalous sound detection is concerned with identifying sounds that deviate
from what is defined as' normal', without explicitly specifying the types of anomalies. A …
from what is defined as' normal', without explicitly specifying the types of anomalies. A …
[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 …
[PDF][PDF] Reframing unsupervised machine condition monitoring as a supervised classification task with outlier-exposed classifiers
P Primus - Tech. Rep., DCASE2020 Challenge, 2020 - dcase.community
This technical report contains a detailed summary of our submissions to the Unsupervised
Detection of Anomalous Sounds for Machine Condition Monitoring (MCM) Task of the IEEE …
Detection of Anomalous Sounds for Machine Condition Monitoring (MCM) Task of the IEEE …
Creating musical features using multi-faceted, multi-task encoders based on transformers
Computational machine intelligence approaches have enabled a variety of music-centric
technologies in support of creating, sharing and interacting with music content. A strong …
technologies in support of creating, sharing and interacting with music content. A strong …
Musicoder: A universal music-acoustic encoder based on transformer
Y Zhao, J Guo - … Modeling: 27th International Conference, MMM 2021 …, 2021 - Springer
Music annotation has always been one of the critical topics in the field of Music Information
Retrieval (MIR). Traditional models use supervised learning for music annotation tasks …
Retrieval (MIR). Traditional models use supervised learning for music annotation tasks …
Low-complexity models for acoustic scene classification based on receptive field regularization and frequency damping
Deep Neural Networks are known to be very demanding in terms of computing and memory
requirements. Due to the ever increasing use of embedded systems and mobile devices with …
requirements. Due to the ever increasing use of embedded systems and mobile devices with …
Tracing back music emotion predictions to sound sources and intuitive perceptual qualities
Music emotion recognition is an important task in MIR (Music Information Retrieval)
research. Owing to factors like the subjective nature of the task and the variation of …
research. Owing to factors like the subjective nature of the task and the variation of …
Towards explaining expressive qualities in piano recordings: Transfer of explanatory features via acoustic domain adaptation
S Chowdhury, G Widmer - ICASSP 2021-2021 IEEE …, 2021 - ieeexplore.ieee.org
Emotion and expressivity in music have been topics of considerable interest in the field of
music information retrieval. In recent years, mid-level perceptual features have been …
music information retrieval. In recent years, mid-level perceptual features have been …