Automatic sound recognition of urban environment events

Theodoros Theodorou, Iosif Mporas, Nikos Fakotakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The audio analysis of speaker’s surroundings has been a first step for several processing systems that enable speaker’s mobility though his daily life. These algorithms usually operate in a short-time analysis decomposing the incoming events in time and frequency domain. In this paper, an automatic sound recognizer is studied, which investigates audio events of interest from urban environment. Our experiments were conducted using a close set of audio events from which well known and commonly used audio descriptors were extracted and models were training using powerful machine learning algorithms. The best urban sound recognition performance was achieved by SVMs with accuracy equal to approximately 93%.

Original languageEnglish
Title of host publicationSpeech and Computer - 17th International Conference, SPECOM 2015, Proceedings
EditorsAndrey Ronzhin, Rodmonga Potapova, Nikos Fakotakis
PublisherSpringer Nature
Pages129-136
Number of pages8
ISBN (Print)9783319231310
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event17th International Conference on Speech and Computer, SPECOM 2015 - Athens, Greece
Duration: 20 Sept 201524 Sept 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9319
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Speech and Computer, SPECOM 2015
Country/TerritoryGreece
CityAthens
Period20/09/1524/09/15

Keywords

  • Automatic sound recognition
  • Dimensionality redundancy
  • Urban environment

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