An Enhanced Temporal Feature Integration Method for Environmental Sound Recognition

Vasileios Bountourakis, Lazaros Vrysis*, Konstantinos Konstantoudakis, Nikolaos Vryzas

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Temporal feature integration refers to a set of strategies attempting to capture the information conveyed in the temporal evolution of the signal. It has been extensively applied in the context of semantic audio showing performance improvements against the standard frame-based audio classification methods. This paper investigates the potential of an enhanced temporal feature integration method to classify environmental sounds. The proposed method utilizes newly introduced integration functions that capture the texture window shape in combination with standard functions like mean and standard deviation in a classification scheme of 10 environmental sound classes. The results obtained from three classification algorithms exhibit an increase in recognition accuracy against a standard temporal integration with simple statistics, which reveals the discriminative ability of the new metrics
Original languageEnglish
Pages (from-to)410-422
Issue number2
Publication statusPublished - May 2019
MoE publication typeA1 Journal article-refereed


  • environmental sound recognition
  • temporal feature integration
  • statistical feature integration
  • semantic audio analysis
  • audio classification


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