title: Microphone Handling Noise: Measurements of Perceptual Threshold and Effects on Audio Quality.
abstract: A psychoacoustic experiment was carried out to test the effects of microphone handling noise on perceived audio quality. Handling noise is a problem affecting both amateurs using their smartphones and cameras, as well as professionals using separate microphones and digital recorders. The noises used for the tests were measured from a variety of devices, including smartphones, laptops and handheld microphones. The signal features that characterise these noises are analysed and presented. The sounds include various types of transient, impact noises created by tapping or knocking devices, as well as more sustained sounds caused by rubbing. During the perceptual tests, listeners auditioned speech podcasts and were asked to rate the degradation of any unwanted sounds they heard. A representative design test methodology was developed that tried to encourage everyday rather than analytical listening. Signal-to-noise ratio (SNR) of the handling noise events was shown to be the best predictor of quality degradation. Other factors such as noise type or background noise in the listening environment did not significantly affect quality ratings. Podcast, microphone type and reproduction equipment were found to be significant but only to a small extent. A model allowing the prediction of degradation from the SNR is presented. The SNR threshold at which 50% of subjects noticed handling noise was found to be 4.2 ± 0.6 dBA. The results from this work are important for the understanding of our perception of impact sound and resonant noises in recordings, and will inform the future development of an automated predictor of quality for handling noise.
authors.affiliation: Acoustics Research Centre, School of Computing Science and Engineering, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Paul
authors.initials: P
authors.lastname: Kendrick
authors.affiliation: Acoustics Research Centre, School of Computing Science and Engineering, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Iain R
authors.initials: IR
authors.lastname: Jackson
authors.affiliation: Acoustics Research Centre, School of Computing Science and Engineering, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Bruno M
authors.initials: BM
authors.lastname: Fazenda
authors.affiliation: Acoustics Research Centre, School of Computing Science and Engineering, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Trevor J
authors.initials: TJ
authors.lastname: Cox
authors.affiliation: Acoustics Research Centre, School of Computing Science and Engineering, University of Salford, Salford, M5 4WT, United Kingdom.
authors.forename: Francis F
authors.initials: FF
authors.lastname: Li
mesh_terms: D000328:Adult; D001307:Auditory Perception; D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D009622:Noise; D011571:Psychoacoustics; D059629:Signal-To-Noise Ratio; D000068997:Smartphone