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Real-Time Study of Language Change×Sociophonetic Analysis×
분야언어학언어학
계열Process / pipelineProcess / pipeline
기원 연도19942006
창시자William Labov (and the variationist tradition)Sociophoneticians (William Labov; Paul Foulkes; Erik R. Thomas)
유형Longitudinal design for observing language change directlyWorkflow correlating acoustic phonetic measurement with social factors
원전Sankoff, G., & Blondeau, H. (2007). Language change across the lifespan: /r/ in Montreal French. Language, 83(3), 560–588. DOI ↗Foulkes, P., Scobbie, J. M., & Watt, D. (2010). Sociophonetics. In W. J. Hardcastle, J. Laver, & F. E. Gibbon (Eds.), The Handbook of Phonetic Sciences (2nd ed., pp. 703–754). Wiley-Blackwell. ISBN: 9781405145909
별칭Real-Time Analysis, Trend and Panel Study, Longitudinal Language Change StudySociophonetics, Sociophonetic Variation Analysis, Phonetic Variation Analysis
관련44
요약The real-time study of language change observes change directly by comparing comparable data from the same speech community gathered at two or more actual points in time. Where apparent-time analysis infers change from age differences in a single snapshot, real-time study watches the community across the calendar, either by drawing a fresh sample of the same community years later (a trend study) or by re-recording the very same individuals (a panel study). It is the gold standard for confirming that a change has occurred and for distinguishing community-wide generational change from change within individual speakers over their lifespan.Sociophonetic analysis sits at the intersection of acoustic phonetics and variationist sociolinguistics. It applies the precise, quantitative measurement of phonetic variables — vowel formants, voice onset time (VOT), the spectral moments of /s/, and many others — to socially structured samples of speech, then correlates those measurements with social factors such as age, social class, gender, ethnicity, and region. The result is a fine-grained, statistically defensible account of how phonetic detail carries social meaning and how it patterns across communities and across time, increasingly built on large-scale, automated measurement.
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