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| Vowel Formant Analysis× | Variationist Sociolinguistics× | |
|---|---|---|
| Domaine | Linguistique | Linguistique |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1952 | 1972 |
| Auteur d'origine≠ | Acoustic phoneticians (Gordon Peterson & Harold Barney) | William Labov |
| Type≠ | Acoustic measurement workflow for vowel quality | Quantitative field study of socially conditioned linguistic variation |
| Source fondatrice≠ | Peterson, G. E., & Barney, H. L. (1952). Control methods used in a study of the vowels. Journal of the Acoustical Society of America, 24(2), 175–184. DOI ↗ | Labov, W. (1972). Sociolinguistic Patterns. University of Pennsylvania Press. ISBN: 9780812210521 |
| Alias | Formant Analysis, Vowel Acoustic Analysis, F1-F2 Vowel Space Analysis | Variationist Analysis, Labovian Sociolinguistics, Quantitative Sociolinguistics |
| Apparentées | 4 | 4 |
| Résumé≠ | Vowel formant analysis is the acoustic measurement workflow for characterizing vowel quality. Vowels are resonances of the vocal tract, and their identity is carried by the formants — the spectral peaks created by those resonances. The first formant F1 is inversely related to vowel height (low F1 for high vowels, high F1 for low vowels), and the second formant F2 tracks frontness/backness (high F2 for front vowels, low F2 for back vowels). By measuring F1 and F2, plotting vowels in the F1×F2 acoustic space, and normalizing across speakers with procedures such as Lobanov, Bark, and Nearey, analysts obtain a reproducible map of a vowel system that can be compared within and across speakers, dialects, and time. | Variationist sociolinguistics is the quantitative study of how linguistic variation is structured by social and linguistic factors. Pioneered by William Labov in the 1960s and 1970s, it treats alternative ways of saying the same thing — the 'linguistic variable' — as systematically conditioned by speaker characteristics (class, age, sex, ethnicity), stylistic context, and the surrounding linguistic environment, and it uses statistical modeling of natural speech to reveal the orderly heterogeneity beneath apparent randomness. |
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