The workshop aims to provide a venue for researchers working on computational analysis of sound events and scene analysis to present and discuss their results.
The 6th Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2021, will be held online on November 15-19.
As in previous years the workshop is organized in conjunction with the DCASE challenge. We aim to bring together researchers from many different universities and companies with an interest in the topic, and provide the opportunity for scientific exchange of ideas and opinions.
The technical program will include invited speakers on the topic of computational everyday sound analysis and recognition, and oral and poster presentations of accepted papers. Additionally, a special poster session will be dedicated to the DCASE 2021 challenge entries and results.
The workshop will be held Online using a combination of virtual platforms that will be announced at a later stage.
We invite submissions on the topics of computational analysis of acoustic scenes and sound events, including but not limited to:
Tasks in computational environmental audio analysis
- Acoustic scene classification
- Sound event detection and localization
- Audio tagging
- Challenges in real-life applications (e.g., rare events, overlapping sound events, and weak labels)
Methods for computational environmental audio analysis
- Signal processing methods
- Machine learning methods
- Auditory-motivated methods
- Cross-disciplinary methods involving, e.g., acoustics, biology, psychology, geography, materials science, transports science
Resources, applications, and evaluation of computational environmental audio analysis
- Publicly available datasets or software, taxonomies and ontologies, evaluation procedures
- Ethics, privacy, responsible research
- Description of systems submitted to the DCASE 2021 Challenge, expanded from the challenge technical report submissions to include more discussions such as ablation studies for additional modules in your method
Reproducible research with open-source code and open data is encouraged (but not mandatory).