Perception and automated assessment of audio quality in user generated content

Fazenda, BM ORCID:, Jackson, I, Kendrick, P ORCID:, Cox, TJ ORCID: and Li, FF ORCID: 2016, 'Perception and automated assessment of audio quality in user generated content' , in: Quality of Multimedia Experience (QoMEX), 2016 Eighth International Conference on 6-8 June 2016 , IEEE.

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Technology to record sound, available in personal devices such as smartphones or video recording devices, is now ubiquitous. However, the production quality of the sound on this user-generated content is often very poor: distorted, noisy, with garbled speech or indistinct music. Our interest lies in the causes of the poor recording, especially what happens between the sound source and the electronic signal emerging from the microphone, and finding an automated method to warn the user of such problems. Typical problems, such as distortion, wind noise, microphone handling noise and frequency response, were tested. A perceptual model has been developed from subjective tests on the perceived quality of such errors and data measured from a training dataset composed of various audio files. It is shown that perceived quality is associated with distortion and frequency response, with wind and handling noise being just slightly less important. In addition, the contextual content of the audio sample was found to modulate perceived quality at similar levels to degradations such as wind and rendering those introduced by handling noise negligible.

Item Type: Book Section
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Publisher: IEEE
ISBN: 9781509003549
Related URLs:
Funders: Engineering and Physical Sciences Research Council (EPSRC)
Depositing User: BM Fazenda
Date Deposited: 17 Nov 2016 11:01
Last Modified: 15 Feb 2022 21:25

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