In this work, we propose an approach that features deep feature embedding learning and
hierarchical classification with triplet loss function for Acoustic Scene Classification (ASC). In …

This report describes our contribution to the development of audio scene classification
methods for the DCASE 2018 Challenge Task 1A. The proposed systems for this task are …

Acoustic scene classification (ASC) is a topic related to the field of machine listening whose
important role is to recognize and categorize audio data in a predefined label which …

This technical report describes the ADSPLAB team's submission for Task1 of DCASE2020
challenge. Our acoustic scene classification (ASC) system is based on the convolutional …

Acoustic scene classification is an intricate problem for a machine. As an emerging field of
research, deep Convolutional Neural Networks (CNN) achieve convincing results. In this …

Deep convolutional neural network (DCNN) has recently improved the performance of
acoustic scene classification. However, the input features of the network are usually based …

Convolutional networks have achieved the state-of-the-art performance on Acoustic Scene
Classification (ASC). Given the Log Mel-Spectrogram of an audio sample, the network can …

Various attention mechanisms are being widely applied to acoustic scene classification.
However, we empirically found that the attention mechanism can excessively discard …

Acoustic scene classification (ASC) is an audio classification task that identifies the
environment in which sounds are recorded. Audio-related machine learning algorithms …

Acoustic scene classification (ASC) has seen tremendous progress from the combined use
of convolutional neural networks (CNNs) and signal processing strategies. In this paper, we …