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Recognizing the quality of urban sound recordings using hand-crafted and deep audio features

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PETRA '19: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments

June 2019

Pages 323 - 324

https://doi.org/10.1145/3316782.3322739

Published: 05 June 2019 Publication History

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Abstract

Soundscape can be regarded as the auditory landscape, conceived individually or at collaborative level. This paper presents a method for automatic recognition of the soundscape quality of urban recordings. Towards this end, the ATHens Urban Soundscape has been used, which is a dataset of audio recordings of ambient urban sounds, annotated in terms of the corresponding perceived soundscape quality. In order to automatically recognize the soundscape quality, both hand-crafted and deep features have been adopted. Experimental results have demonstrated that the performance of the final classifier that combines hand-crafted and deep context-aware audio features is boosted by almost 2%.

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Luo LZhang QMao YPeng YWang TXu J(2023)A Study on the Soundscape Preferences of the Elderly in the Urban Forest Parks of Underdeveloped Cities in ChinaForests10.3390/f1406126614:6(1266)Online publication date: 19-Jun-2023
https://doi.org/10.3390/f14061266
Chaki J(2020)Pattern analysis based acoustic signal processing: a survey of the state-of-artInternational Journal of Speech Technology10.1007/s10772-020-09681-3Online publication date: 3-Feb-2020
https://doi.org/10.1007/s10772-020-09681-3

Recognizing the quality of urban sound recordings using hand-crafted and deep audio features
1. Applied computing
  1. Arts and humanities

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Published In

PETRA '19: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments

June 2019

655 pages

ISBN:9781450362320

DOI:10.1145/3316782

Conference Chair:
Fillia Makedon
University of Texas at Arlington

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 05 June 2019

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PETRA '19: The 12th PErvasive Technologies Related to Assistive Environments Conference

June 5 - 7, 2019

Rhodes, Greece

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Luo LZhang QMao YPeng YWang TXu J(2023)A Study on the Soundscape Preferences of the Elderly in the Urban Forest Parks of Underdeveloped Cities in ChinaForests10.3390/f1406126614:6(1266)Online publication date: 19-Jun-2023
https://doi.org/10.3390/f14061266
Chaki J(2020)Pattern analysis based acoustic signal processing: a survey of the state-of-artInternational Journal of Speech Technology10.1007/s10772-020-09681-3Online publication date: 3-Feb-2020
https://doi.org/10.1007/s10772-020-09681-3

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Sound image externalization for headphone based real-time 3D audio

Enhancement of Spatial Sound Quality: A New Reverberation-Extraction Audio Upmixer

A Study on Realistic Audio Sound Generation according to User's Movement in Virtual Reality System

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Sound image externalization for headphone based real-time 3D audio

Enhancement of Spatial Sound Quality: A New Reverberation-Extraction Audio Upmixer

A Study on Realistic Audio Sound Generation according to User's Movement in Virtual Reality System

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