Skip to content

The official implementations of our DCASE 2021 task 1a

Notifications You must be signed in to change notification settings

Yunlei-AI/DCASE2021

 
 

Repository files navigation

DCASE2021

This repository is the official implementations of our DCASE 2021 task 1a with technical report:

Soonshin Seo, Ji-Hwan Kim: "MobileNet using Coordinate Attention and Fusions for Low-Complexity Acoustic Scene Classification with Multiple Devices", submitted to task 1a of the 2021 DCASE Challenge

A technical report link at (http://dcase.community/documents/challenge2021/technical_reports/DCASE2021_Seo_52_t1.pdf)

Training

  1. Download the development dataset form links at https://zenodo.org/record/3819968#.YLiqhfkzaUk
  2. Use the script "feats.py" & data augmentation scripts
  3. Use the script "train.py"

Quantization & Evauation

  1. Use the script "run.sh"

Main methods

  1. Normalization & data augmentations
  2. MobileNet
  3. Cooridnate attention
  4. Early fusion & late fusion

Acknowledgement

We used the implementation presented in https://github.com/MihawkHu/DCASE2020_task1 as our baseline script.

Bibtex

@techreport{Seo_DCASE2021,
  author    = {Soonshin Seo, Ji-Hwan Kim},
  title     = {MobileNet using Coordinate Attention and Fusions for Low-Complexity Acoustic Scene Classification with Multiple Devices},
  institution = {DCASE2021 Challenge},
  year      = {2021},
}

About

The official implementations of our DCASE 2021 task 1a

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 99.6%
  • Shell 0.4%