Article ID Journal Published Year Pages File Type
6861063 International Journal of Human-Computer Studies 2016 11 Pages PDF
Abstract
Recordings of the Earth's surface oscillation as a function of time (seismograms) can be sonified by compressing time so that most of the signal's frequency spectrum falls in the audible range. The pattern-recognition capabilities of the human auditory system can then be applied to the auditory analysis of seismic data. In this experiment, we sonify a set of seismograms associated with a magnitude-5.6 Oklahoma earthquake recorded at 17 broadband stations within a radius of ∼300 km from the epicenter, and a group of volunteers listen to our sonified seismic data set via headphones. Most of the subjects have never heard a sonified seismogram before. Given the lack of studies on this subject, we prefer to make no preliminary hypotheses on the categorization criteria employed by the listeners: we follow the “free categorization” approach, asking listeners to simply group sounds that they perceive as “similar.” We find that listeners tend to group together sonified seismograms sharing one or more underlying physical parameters, including source-receiver distance, source-receiver azimuth, and, possibly, crustal structure between source and receiver and/or at the receiver. This suggests that, if trained to do so, human listeners can recognize subtle features in sonified seismic signals. It remains to be determined whether auditory analysis can complement or lead to improvements upon the standard visual and computational approaches in specific tasks of geophysical interest.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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