Effects of Temporal and Spectral Combinations on the Judged Noisiness of Aircraft Sounds

Pearsons, Karl S.; Bennett, Ricarda L.

doi:10.1121/1.1912462

Cited by 5 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The judgments of people asked under controlled listening conditions to compare the annoyance of artificial or irrelevant sounds such as tones and bands of noise are well predicted by spectral weighting procedures. For example, A-level is consistently found to be superior to unweighted (overall) noise metric as a predictor of annoyance 3,4 and measures such as Effective Perceived Noise Level account well for the effects of signal duration on annoyance.…”

Section: Introductionmentioning

confidence: 96%

Insufficiency of an environmental sound's power spectrum as a predictor of its annoyance

Fidell¹,

Sneddon²,

Pearsons³

et al. 2002

Noise Control Eng. J.

View full text Add to dashboard Cite

The annoyance of environmental noise exposure and its "acceptability" with respect to land use compatibility and other interpretive criteria are routinely assessed in terms of assorted frequencyweighted noise metrics. Although laboratory measurements have established the utility of frequency-weighting networks and more complex procedures as predictors of the judged annoyance of sounds heard under controlled listening conditions, many factors can erode the predictive utility of noise metrics in residential settings. For example, relationships between Aweighted noise levels and the prevalence of annoyance due to environmental noise exposure typically account for less than half of the variance in community survey information about the prevalence of noise-induced annoyance. The current study indicates that even under controlled listening conditions, the spectral distribution of sound energy is not a fully sufficient predictor of the annoyance of transportation noise. This finding suggests a fundamental limitation on the generality of predictions of the annoyance of environmental noise exposure that are based on acoustic information alone. ©2002 Institute of Noise Control Engineering.

show abstract

Section: Introductionmentioning

confidence: 96%

Insufficiency of an environmental sound's power spectrum as a predictor of its annoyance

Fidell¹,

Sneddon²,

Pearsons³

et al. 2002

Noise Control Eng. J.

View full text Add to dashboard Cite

show abstract

“…However, the magnitude of the effect varies widely from study to study (e.g., Kryter and Pearsons 1965;Little and Mabry 1969;Pearsons and Bennett 1971). However, the magnitude of the effect varies widely from study to study (e.g., Kryter and Pearsons 1965;Little and Mabry 1969;Pearsons and Bennett 1971).…”

Section: Heating Ventilating and Air Conditioning (Hvac) Noisementioning

confidence: 99%

Neurally Based Measurement and Evaluation of Environmental Noise

Soeta

Ando

2015

Mathematics for Industry

View full text Add to dashboard Cite

Aims & ScopeThe meaning of "Mathematics for Industry" (sometimes abbreviated as MI or MfI) is different from that of "Mathematics in Industry" (or of "Industrial Mathematics"). The latter is restrictive: it tends to be identified with the actual mathematics that specifically arises in the daily management and operation of manufacturing. The former, however, denotes a new research field in mathematics that may serve as a foundation for creating future technologies. This concept was born from the integration and reorganization of pure and applied mathematics in the present day into a fluid and versatile form capable of stimulating awareness of the importance of mathematics in industry, as well as responding to the needs of industrial technologies. The history of this integration and reorganization indicates that this basic idea will someday find increasing utility. Mathematics can be a key technology in modern society.The series aims to promote this trend by (1) providing comprehensive content on applications of mathematics, especially to industry technologies via various types of scientific research, (2) introducing basic, useful, necessary and crucial knowledge for several applications through concrete subjects, and (3) introducing new research results and developments for applications of mathematics in the real world. These points may provide the basis for opening a new mathematicsoriented technological world and even new research fields of mathematics.More information about this series at

show abstract

Annoyance of Noise

Soeta

Ando

2015

Neurally Based Measurement and Evaluation of Environmental Noise

View full text Add to dashboard Cite

Effects of Temporal and Spectral Combinations on the Judged Noisiness of Aircraft Sounds

Cited by 5 publications

References 0 publications

Insufficiency of an environmental sound's power spectrum as a predictor of its annoyance

Insufficiency of an environmental sound's power spectrum as a predictor of its annoyance

Neurally Based Measurement and Evaluation of Environmental Noise

Annoyance of Noise

Contact Info

Product

Resources

About