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Vowels vary in their acoustic similarity across regional dialects of American English, such that some vowels are more similar to one another in some dialects than others. Acoustic vowel distance measures typically evaluate vowel similarity at a discrete time point, resulting in distance estimates that may not fully capture vowel similarity in formant trajectory dynamics. In the current study, language and accent distance measures, which evaluate acoustic distances between talkers over time, were applied to the evaluation of vowel category similarity within talkers. These vowel category distances were then compared across dialects, and their utility in capturing predicted patterns of regional dialect variation in American English was examined. Dynamic time warping of mel-frequency cepstral coefficients was used to assess acoustic distance across the frequency spectrum and captured predicted Southern American English vowel similarity. Root-mean-square distance and generalized additive mixed models were used to assess acoustic distance for selected formant trajectories and captured predicted Southern, New England, and Northern American English vowel similarity. Generalized additive mixed models captured the most predicted variation, but, unlike the other measures, do not return a single acoustic distance value. All three measures are potentially useful for understanding variation in vowel category similarity across dialects. 

Online data collection allows for access to diverse populations. In the current study, we used online recruitment and data collection methods to obtain a corpus of read speech from adult talkers representing three authentic regional dialects of American English and one novel dialect created for the corpus. The authentic dialects (New England, Northern, and Southern American English) are each represented by 8–10 talkers, ranging in age from 22 to 75 years old. The novel dialect was produced by five Spanish-English bilinguals with training in linguistics, who were asked to produce Spanish /o/ in an otherwise English segmental context. One vowel contrast was selected for each dialect, in which the vowels within the contrast are acoustically more similar in the target dialect than in the other dialects. Each talker produced one familiar short story with 40 tokens of each vowel within the target contrast for their dialect, as well as a set of real words and nonwords that represent both the target vowel contrast for their dialect and the other three vowel contrasts for comparison across dialects. Preliminary acoustic analysis reveals both cross-dialect and within-dialect variability in the target vowel contrasts. The corpus materials are available to the scholarly community.