Recent advancements in modeling speech and audio signals using deep neural networks
have shown that systems learning both features and the classifier can be built directly from …

Acoustic scene classification (ASC) aims to analyse the recording scene of a piece of audio.
In real life, ASC has to deal with audio data from various recording devices, even those …

Acoustic scene classification systems using deep neural networks classify given recordings
into pre-defined classes. In this study, we propose a novel scheme for acoustic scene …

This technical report presents our submitted system for the DCASE 2021 Challenge Task1B:
Audio-Visual Scene Classification. Focusing on the audio modality only, we investigate the …

This technical report describes our Acoustic Scene Classification systems for DCASE2020
challenge Task1. For subtask A, we designed a single model implemented with three …

Frequently misclassified pairs of classes that share many common acoustic properties exist
in acoustic scene classification (ASC). To distinguish such pairs of classes, trivial details …

Automatic understanding of audio events and acoustic scenes has been an active research
topic for researchers from signal processing and machine learning communities …

We investigate the problem of acoustic scene classification, using a deep residual network
applied to log-mel spectrograms complemented by log-mel deltas and delta-deltas. We …

In this report, we describes the SHNU team's submission to the DCASE-2020 challenge
Task1-A (Acoustic Scene Classification with Multiple Devices). In our submissions, three …

Acoustic scene classification (ASC) is the process of identifying the acoustic environment or
scene from which an audio signal is recorded. In this work, we propose an encoder-decoder …