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      Articulation of vowel length contrasts in Australian English

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          Abstract

          Acoustic studies have shown that in Australian English (AusE), vowel length contrasts are realised through temporal, spectral and dynamic characteristics. However, relatively little is known about the articulatory differences between long and short vowels in this variety. This study investigates the articulatory properties of three long–short vowel pairs in AusE: /iː–ɪ/ beatbit, /ɐː–ɐ/ cartcutand /oː–ɔ/ portpot, using electromagnetic articulography. Our findings show that short vowel gestures had shorter durations and more centralised articulatory targets than their long equivalents. Short vowel gestures also had proportionately shorter periods of articulatory stability and proportionately longer articulatory transitions to following consonants than long vowels. Long–short vowel pairs varied in the relationship between their acoustic duration and the similarity of their articulatory targets: /iː–ɪ/ had more similar acoustic durations and less similar articulatory targets, while /ɐː–ɐ/ were distinguished by greater differences in acoustic duration and more similar articulatory targets. These data suggest that the articulation of vowel length contrasts in AusE may be realised through a complex interaction of temporal, spatial and dynamic kinematic cues.

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              Random effects structure for confirmatory hypothesis testing: Keep it maximal.

              Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F 1 and F 2 tests, and in many cases, even worse than F 1 alone. Maximal LMEMs should be the 'gold standard' for confirmatory hypothesis testing in psycholinguistics and beyond.
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                Author and article information

                Contributors
                Journal
                Journal of the International Phonetic Association
                Journal of the International Phonetic Association
                Cambridge University Press (CUP)
                0025-1003
                1475-3502
                May 05 2022
                : 1-30
                Article
                10.1017/S0025100322000068
                9a204334-669c-4dc7-93ea-cff969cceed2
                © 2022

                Free to read

                http://creativecommons.org/licenses/by/4.0/

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