Two-Stage Classification Learning for Open Set Acoustic Scene Classification

Chunxia Ren, Shengchen Li*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)


Most of the research on acoustic scene classification (ASC) focuses on classification problem with only known scene classes. In practice, scene classification problem to be solved generally is based on an open set, which contains unknown scenes. This paper proposes a two-stage method that solves the open set problem on ASC. The proposed system decomposes open set ASC problem into two stages. To mitigate the impact of unknown scenes on the subsequent recognition process of known scenes, the first stage is to identify unknown scenes. The second stage classifies defined acoustic scenes. In this case, the threshold selection strategy we proposed further sorts out unknown scenes that were not identified in the previous stage. Experiments show that the method proposed in this paper can effectively identify unknown scenes and classify known scenes, by segmenting the open set acoustic scene classification task and selecting an appropriate judgment threshold. On the development dataset released by DCASE Challenge 2019 Task 1C, the model proposed outperforms the first place.

Original languageEnglish
Title of host publicationProceedings of the 8th Conference on Sound and Music Technology - Selected Papers from CSMT
EditorsXi Shao, Kun Qian, Li Zhou, Xin Wang, Ziping Zhao
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9789811616488
Publication statusPublished - 2021
Event8th Conference on Sound and Music Technology, CSMT 2020 - Taiyuan, China
Duration: 5 Nov 20208 Nov 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume761 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


Conference8th Conference on Sound and Music Technology, CSMT 2020


  • Acoustic scene classification
  • Open set
  • Threshold selection strategy
  • Two-stage classification

Cite this