Data_Sheet_1_Language Adapts to Environment: Sonority and Temperature.docx
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
The phonetic patterns of human spoken languages have been claimed to be in part shaped by environmental conditions in the locales where they are spoken. This follows predictions of the Acoustic Adaptation Hypothesis, previously mainly applied to the study of bird song, which proposes that differential transmission conditions in different environments explain some of the frequency and temporal variation between and within species' songs. Prior discussion of the relevance of the Acoustic Adaptation Hypothesis to human language has related such characteristics as the total size of the consonant inventory and the complexity of the permitted maximum syllable structure, rather than patterns in continuous speech, to environmental variables. Thus the relative frequency with which more complex structures occur is not taken into account. This study looks at brief samples of spoken material from 100 languages, dividing the speech into sonorous and obstruent time fractions. The percentage of sonorous material is the sonority score. This score correlates quite strongly with mean annual temperature in the area where the languages are spoken, with higher temperatures going together with higher sonority scores. The role of tree cover and annual precipitation, found to be important in earlier work, is not found to be significant in this data. This result may be explained if absorption and scattering are more important than reflection. Atmospheric absorption is greater at higher temperatures and peaks at higher frequencies with increasing temperature. Small-scale local perturbations (eddies) in the atmosphere created by high air temperatures also degrade the high-frequency spectral characteristics that are critical to distinguishing between obstruent consonants, leading to reduction in contrasts between them, and fewer clusters containing obstruent strings.
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