Sound Event Detection: A tutorial

Annamaria Mesaros; Toni Heittola; Tuomas Virtanen; Mark D. Plumbley

doi:10.1109/MSP.2021.3090678

Sound Event Detection: A tutorial

Annamaria Mesaros, Toni Heittola, Tuomas Virtanen, Mark D. Plumbley

Computing Sciences

Research output: Contribution to journal › Article › Scientific › peer-review

2 Downloads (Pure)

Abstract

Imagine standing on a street corner in the city. With your eyes closed you can hear and recognize a succession of sounds: cars passing by, people speaking, their footsteps when they walk by, and the continuous falling of rain. The recognition of all these sounds and interpretation of the perceived scene as a city street soundscape comes naturally to humans. It is, however, the result of years of "training": encountering and learning associations among the vast varieties of sounds in everyday life, the sources producing these sounds, and the names given to them.

Original language	English
Pages (from-to)	67-83
Number of pages	17
Journal	IEEE Signal Processing Magazine
Volume	38
Issue number	5
DOIs	https://doi.org/10.1109/MSP.2021.3090678
Publication status	Published - 2021
Publication type	A1 Journal article-refereed

Keywords

Acoustics
Urban areas
Tutorials

Publication forum classification

Publication forum level 3

Access to Document

10.1109/MSP.2021.3090678

SED_tutorial_IEEE_SPM_mesaros-1
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Accepted author manuscript, 2.94 MBLicence: Unspecified

https://urn.fi/URN:NBN:fi:tuni-202301251701Licence: Unspecified

Cite this

@article{774c9c35ed9549749d4a8acc57ac07b9,

title = "Sound Event Detection: A tutorial",

abstract = "Imagine standing on a street corner in the city. With your eyes closed you can hear and recognize a succession of sounds: cars passing by, people speaking, their footsteps when they walk by, and the continuous falling of rain. The recognition of all these sounds and interpretation of the perceived scene as a city street soundscape comes naturally to humans. It is, however, the result of years of {"}training{"}: encountering and learning associations among the vast varieties of sounds in everyday life, the sources producing these sounds, and the names given to them.",

keywords = "Acoustics, Urban areas, Tutorials",

author = "Annamaria Mesaros and Toni Heittola and Tuomas Virtanen and Plumbley, {Mark D.}",

year = "2021",

doi = "10.1109/MSP.2021.3090678",

language = "English",

volume = "38",

pages = "67--83",

journal = "IEEE Signal Processing Magazine",

issn = "1053-5888",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "5",

}

TY - JOUR

T1 - Sound Event Detection: A tutorial

AU - Mesaros, Annamaria

AU - Heittola, Toni

AU - Virtanen, Tuomas

AU - Plumbley, Mark D.

PY - 2021

Y1 - 2021

N2 - Imagine standing on a street corner in the city. With your eyes closed you can hear and recognize a succession of sounds: cars passing by, people speaking, their footsteps when they walk by, and the continuous falling of rain. The recognition of all these sounds and interpretation of the perceived scene as a city street soundscape comes naturally to humans. It is, however, the result of years of "training": encountering and learning associations among the vast varieties of sounds in everyday life, the sources producing these sounds, and the names given to them.

AB - Imagine standing on a street corner in the city. With your eyes closed you can hear and recognize a succession of sounds: cars passing by, people speaking, their footsteps when they walk by, and the continuous falling of rain. The recognition of all these sounds and interpretation of the perceived scene as a city street soundscape comes naturally to humans. It is, however, the result of years of "training": encountering and learning associations among the vast varieties of sounds in everyday life, the sources producing these sounds, and the names given to them.

KW - Acoustics

KW - Urban areas

KW - Tutorials

U2 - 10.1109/MSP.2021.3090678

DO - 10.1109/MSP.2021.3090678

M3 - Article

SN - 1053-5888

VL - 38

SP - 67

EP - 83

JO - IEEE Signal Processing Magazine

JF - IEEE Signal Processing Magazine

IS - 5

ER -

Sound Event Detection: A tutorial

Abstract

Keywords

Publication forum classification

Access to Document

Fingerprint

Cite this