title: Perception and automatic detection of wind-induced microphone noise.
abstract: Wind can induce noise on microphones, causing problems for users of hearing aids and for those making recordings outdoors. Perceptual tests in the laboratory and via the Internet were carried out to understand what features of wind noise are important to the perceived audio quality of speech recordings. The average A-weighted sound pressure level of the wind noise was found to dominate the perceived degradation of quality, while gustiness was mostly unimportant. Large degradations in quality were observed when the signal to noise ratio was lower than about 15 dB. A model to allow an estimation of wind noise level was developed using an ensemble of decision trees. The model was designed to work with a single microphone in the presence of a variety of foreground sounds. The model outputted four classes of wind noise: none, low, medium, and high. Wind free examples were accurately identified in 79% of cases. For the three classes with noise present, on average 93% of samples were correctly assigned. A second ensemble of decision trees was used to estimate the signal to noise ratio and thereby infer the perceived degradation caused by wind noise.
authors.affiliation: Acoustics Research Centre, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Iain R
authors.initials: IR
authors.lastname: Jackson
authors.affiliation: Acoustics Research Centre, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Paul
authors.initials: P
authors.lastname: Kendrick
authors.affiliation: Acoustics Research Centre, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Trevor J
authors.initials: TJ
authors.lastname: Cox
authors.affiliation: Acoustics Research Centre, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Bruno M
authors.initials: BM
authors.lastname: Fazenda
authors.affiliation: Acoustics Research Centre, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Francis F
authors.initials: FF
authors.lastname: Li
mesh_terms: D000161:Acoustic Stimulation; D000162:Acoustics / Q000295:instrumentation*; D000328:Adult; D000465:Algorithms; D001302:Audiometry, Speech; D001331:Automation; D003663:Decision Trees; D006801:Humans; D008962:Models, Theoretical; D009038:Motion; D009622:Noise; D010470:Perceptual Masking; D011312:Pressure; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D013067:Speech Perception; D013997:Time Factors; D014160:Transducers, Pressure; D014919:Wind; D055815:Young Adult