Acoustic scene classification : An overview of dcase 2017 challenge entries
Mesaros, Annamaria; Heittola, Toni; Virtanen, Tuomas (2018-11-02)
Mesaros, Annamaria
Heittola, Toni
Virtanen, Tuomas
IEEE
02.11.2018
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202105104705
https://urn.fi/URN:NBN:fi:tuni-202105104705
Kuvaus
Peer reviewed
Tiivistelmä
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.
Kokoelmat
- TUNICRIS-julkaisut [16983]