It is a practical research topic how to deal with multi-device audio inputs by a single acoustic
scene classification system with efficient design. In this work, we propose Residual …

Recently, convolutional neural networks (CNN) have achieved the state-of-the-art
performance in acoustic scene classification (ASC) task. The audio data is often transformed …

Convolutional neural networks with time-frequency feature representation for acoustic scene
classification have been attracting increasing attentions. However, most of the existing …

Acoustic scene classification (ASC) is a problem related to the field of machine listening
whose objective is to classify/tag an audio clip in a predefined label describing a scene …

To improve device robustness, a highly desirable key feature of a competitive data-driven
acoustic scene classification (ASC) system, a novel two-stage system based on fully …

In this technical report, we present a joint effort of four groups, namely GT, USTC, Tencent,
and UKE, to tackle Task 1-Acoustic Scene Classification (ASC) in the DCASE 2020 …

Spectrogram representations of acoustic scenes have achieved competitive performance for
acoustic scene classification. Yet, the spectrogram alone does not take into account a …

Acoustic scene classification (ASC) aims to classify an audio clip based on the characteristic
of the recording environment. In this regard, deep learning based approaches have …

This technical report describes the Task 1-Subtask A (Acoustic Scene Classification, ASC) of
the DCASE 2019 challenge whose goal is to classify a test audio recording into one of the …

Audio scene classification, the problem of predicting class labels of audio scenes, has
drawn lots of attention during the last several years. However, it remains challenging and …