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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Kendrick, P; Jackson, IR; Li, FF; Fazenda, BM; Cox, TJ
Publisher: Audio Engineering Society
Languages: English
Types: Article
Subjects: media_dig_tech_and_creative_econ
For field recordings and user generated content recorded on phones, tablets, and other mobile\ud devices nonlinear distortions caused by clipping and limiting at pre-amplification stages, and\ud dynamic range control (DRC) are common causes of poor audio quality. A single-ended\ud method to detect these distortions and predict perceived degradation in speech, music, and\ud soundscapes has been developed. This was done by training an ensemble of decision trees.\ud During training, both clean and distorted audio was available and so the perceived quality\ud could be gauged using HASQI (Hearing Aid Sound Quality Index). The new single-ended\ud method can correctly predict HASQI from distorted samples to an accuracy of ±0.19 (95%\ud confidence interval) using a quality range between 0.0 and 1.0. The method also has potential\ud for estimating HASQI when other types of degradations are present. Subsequent perceptual\ud tests validated the method for music and soundscapes. For the average mean opinion score\ud for perceived audio quality on a scale from 0 to 1, the single ended method could estimate it\ud within ±0.33.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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