Abstract
We present an overview of the challenge entries for the Acoustic Scene Classification task of DCASE 2017 Challenge. Being the most popular task of the challenge, acoustic scene classification entries provide a wide variety of approaches for comparison, with a wide performance gap from top to bottom. Analysis of the submissions confirms once more the popularity of deep-learning approaches and mel frequency representations. Statistical analysis indicates that the top ranked system performed significantly better than the others, and that combinations of top systems are capable of reaching close to perfect performance on the given data.
Original language | English |
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Title of host publication | 16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 |
Publisher | IEEE |
Pages | 411-415 |
Number of pages | 5 |
ISBN (Electronic) | 9781538681510 |
DOIs | |
Publication status | Published - 2 Nov 2018 |
Publication type | A4 Article in conference proceedings |
Event | International Workshop on Acoustic Signal Enhancement - Tokyo, Japan Duration: 17 Sept 2018 → 20 Sept 2018 |
Conference
Conference | International Workshop on Acoustic Signal Enhancement |
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Country/Territory | Japan |
City | Tokyo |
Period | 17/09/18 → 20/09/18 |
Keywords
- Acoustic scene classification
- Audio classb ification
- DCASE challenge
Publication forum classification
- Publication forum level 1
ASJC Scopus subject areas
- Signal Processing
- Acoustics and Ultrasonics