Literature DB >> 28372076

Auditory display of seismic data: On the use of experts' categorizations and verbal descriptions as heuristics for geoscience.

Arthur Paté1, Lapo Boschi2, Danièle Dubois1, Jean-Loïc Le Carrou1, Benjamin Holtzman3.   

Abstract

Auditory display can complement visual representations in order to better interpret scientific data. A previous article showed that the free categorization of "audified seismic signals" operated by listeners can be explained by various geophysical parameters. The present article confirms this result and shows that cognitive representations of listeners can be used as heuristics for the characterization of seismic signals. Free sorting tests are conducted with audified seismic signals, with the earthquake/seismometer relative location, playback audification speed, and earthquake magnitude as controlled variables. The analysis is built on partitions (categories) and verbal comments (categorization criteria). Participants from different backgrounds (acousticians or geoscientists) are contrasted in order to investigate the role of the participants' expertise. Sounds resulting from different earthquake/station distances or azimuths, crustal structure and topography along the path of the seismic wave, earthquake magnitude, are found to (a) be sorted into different categories, (b) elicit different verbal descriptions mainly focused on the perceived number of events, frequency content, and background noise level. Building on these perceptual results, acoustic descriptors are computed and geophysical interpretations are proposed in order to match the verbal descriptions. Another result is the robustness of the categories with respect to the audification speed factor.

Entities:  

Year:  2017        PMID: 28372076     DOI: 10.1121/1.4978441

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  1 in total

1.  Machine learning reveals cyclic changes in seismic source spectra in Geysers geothermal field.

Authors:  Benjamin K Holtzman; Arthur Paté; John Paisley; Felix Waldhauser; Douglas Repetto
Journal:  Sci Adv       Date:  2018-05-23       Impact factor: 14.136

  1 in total

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