754 citations · 3.2k across the 112 of their papers we have counts for
4 papers · 2 filters
ARCA23K: An audio dataset for investigating open-set label noise
Turab Iqbal, Yin Cao, Andrew Bailey +2
The availability of audio data on sound sharing platforms such as Freesound gives users access to large amounts of annotated audio. Utilising such data for training is becoming inc…
Using UMAP to Inspect Audio Data for Unsupervised Anomaly Detection under Domain-Shift Conditions
Andres Fernandez, Mark D. Plumbley
The goal of Unsupervised Anomaly Detection (UAD) is to detect anomalous signals under the condition that only non-anomalous (normal) data is available beforehand. In UAD under Doma…
Federated Learning With Highly Imbalanced Audio Data
Marc C. Green, Mark D. Plumbley
Federated learning (FL) is a privacy-preserving machine learning method that has been proposed to allow training of models using data from many different clients, without these cli…
An Audio-Based Deep Learning Framework For BBC Television Programme Classification
Lam Pham, Chris Baume, Qiuqiang Kong +3
This paper proposes a deep learning framework for classification of BBC television programmes using audio. The audio is firstly transformed into spectrograms, which are fed into a…