Multidimensional acoustic variation in vowels across E nglish dialects (2022)

Abstract: Vowels are typically characterized in terms of their static position in formant space, though vowels have also been long-known to undergo dynamic formant change over their timecourse. Recent studies have demonstrated that this change is highly informative for distinguishing vowels within a system, as well as providing additional resolution in characterizing differences between dialects. It remains unclear, however, how both static and dynamic representations capture the main dimensions of vowel variation across a large number of dialects. This study examines the role of static, dynamic, and duration information for 5 vowels across 21 British and North American English dialects, and observes that vowels exhibit highly structured variation across dialects, with dialects displaying similar patterns within a given vowel, broadly corresponding to a spectrum between traditional ‘monophthong’ and ‘diphthong’ characterizations. These findings highlight the importance of dynamic and duration information in capturing how vowels can systematically vary across a large number of dialects, and provide the first large-scale description of formant dynamics across many dialects of a single language.

## introduction both the classification and measurement of vowels have long been central, intersecting, issues for phonetic research. vowels are dynamic in production, yet language-specific vowel descriptions typically use broad categories referring to more or less general 'movement' of a vowel, such as distinguishing between monophthongal and diphthongal vowel realizations. at the same time, it is still unclear in what low-dimensional space vowels themselves vary: which acoustic properties best capture differences between vowels, and how securely categories like 'monophthong' and 'diphthong' can be established empirically within and across languages. do these discrete categories reflect the ways in which vowels vary, or are vowel distinctions better characterized by a spectrum, reflecting various degrees of 'movement'? this study addresses this question by examining vowel variation within a languageacross dialects -to consider how both static and dynamic properties of vowels capture dialectal variation across english. static measurements of formants, taken at a single time-point within the vowel, have long provided useful approximations for cues to vowel properties such as height and backness (e.g. @xcite , and have been central to previous descriptions of how vowels vary across dialects (e.g., @xcite @xcite . beyond single-point measurements of vowels, however, the importance of time-dependent dynamic information -such as spectral change and duration -has also been recognized since the earliest phonetic studies of vowel production and perception (e.g. @xcite @xcite . research on english has shown that this dynamic information may be utilized for better distinguishing vowels within a language @xcite @xcite , can reflect detailed dialectal and sociolinguistic meaning @xcite @xcite , play a role in the development of dialect-specific vowel shifts @xcite @xcite @xcite , and constitute a robust source of variation across speakers (e.g. @xcite . studies on single dialects have demonstrated that vowels vary in their average duration @xcite @xcite , though our understanding of how vowel durations systematically vary across dialects is relatively limited (e.g., @xcite @xcite . looking across many english dialects, however, it still remains unclear how best to characterize, on one hand, vowel variability across multiple acoustic dimensions (including how robustly monophthong/diphthong categories hold up across dialects), and on the other hand, the extent to which dynamic representations compare with static measures for characterizing differences between dialects on the basis of vowel realization. this study takes a computational and exploratory approach to addressing these issues, by considering the following research question: to what extent do dynamic representations of vowels (formant trajectories, duration) capture additional information (over static f1/f2 position) in describing vowel variation across english dialects? concretely, answers to this question are addressed in two ways: 1. through an exploratory analysis of english vowel variability (section 3.1), which enables inspection of the 'same' vowel across different dialects, including the evidence for monophthong/diphthong classification; 2. through a dialect classification experiment, where different combinations of formant position, trajectory shape, and duration are compared in their ability to correctly classify the dialect of a given vowel (section 3.2). the exploratory analysis is motivated by the phonetic literature discussed above, which uses formant dynamics to characterize the vowel space of a given dialect, while the classification experiment is inspired by by the computational literature on dialect classification, where different kinds of acoustic information have been found to independently help differentiate dialects (e.g. @xcite @xcite . the study takes a 'large-scale' approach, through the consistent extraction of the same measures for a large amount of data collected from speech corpora of 21 english dialects. scaling up the analysis across multiple dialects is made possible by tools for automatic annotation (e.g. @xcite @xcite , acoustic analysis @xcite , and integrating information across idiosyncratic data formats @xcite . to our knowledge, this is the largest crossdialect study to date of formant dynamics. vowels for the study were selected to provide a spectrum of qualities which are described in the english dialectological literature as ranging from largely monophthongal through to usually diph-thongal, varying dialectally by the presence of a glide @xcite , reflected in the degree of formant change over their timecourse. specifically, the vowels were the following, as represented in terms of lexical sets (a characteristic word of a particular vowel) @xcite : fleece, face, price, mouth, and choice. fleece is expected to be monophthongal across dialects; mouth, price, and choice are expected to be diphthongs, which vary across dialects in both the degree of dynamic change and overall position (e.g. 'monophthongization' of price in southern us varieties, 'canadian raising' of mouth in some canadian/us varieties @xcite @xcite . face is expected to be intermediate between monophthongs and diphthongs, dependent on the specific dialect (e.g. @xcite @xcite . ## data this study examines variation in stressed vowels from 21 british and north american english dialects, using corpus data collated as part of the speech across dialects of english (spade) project @xcite , https://spade.glasgow.ac.uk/ ), including multidialect corpora from the united kingdom @xcite @xcite and north america @xcite , as well as multiple individual english dialect corpora @xcite @xcite @xcite . here, north american dialects refers to dialects in canada and the united states as outlined in the atlas of north american english @xcite . due to the relative sparsity of canadian data compared with united states and british dialects, canadian dialects were distinguished along rural and urban dimensions instead of geographical location @xcite . dialectal distinctions for british english used @xcite modern dialectal groupings, based on both phonological and lexical distinctions. speakers for scottish dialects were grouped based on information from the scottish national dictionary @xcite . tokens with a duration shorter than 50 milliseconds were not extracted, in line with previous studies of vowel formants @xcite length figure 1 : schematic of all dynamic measures (dashed lines) used in the study mapped to a hypothetical choice vowel trajectory (solid line). in order to inspect spectral change across dialects more easily, and to allow comparison of our exploratory formant-based analyses with existing cross-dialect research (section 3.1), we calculated a set of measures which are based on calculations of 'vowel section length' (vsl): the euclidean distance between two formant points (n, m): a measure of the overall spectral change (called 'vector length') is derived from calculating the vsl of the vowel onset and offset, whilst more complex representations of the trajectory can be derived from the summation of vsls calculated from subsets of the points, such as onset to midpoint + midpoint to offset @xcite . figure 1 illustrates these measures on a hypothetical formant trajectory. a wide range of measures have been utilized within the vowel dynamic literature for capturing the dynamic properties of a formant trajectory, such as polynomial functions @xcite @xcite , discrete cosine transforms @xcite , target-locus scaling @xcite , and additive models @xcite ) -the choice to use vector-based measurements of formant trajectories was motivated by their use in numerous studies of dialectal variation in english @xcite @xcite and other languages @xcite . whilst these methods have not been explicitly compared, the decision to make use of the vector-based measurements in this study is based around the relative comparability with the previous cross-dialectal work using this measure, as well as its relative interpretability as a representation of spectral change. more information about the data, vowel formant extraction, and measurement calculation methods used in this study can be found in tanner (2020). in total, 323,060 tokens (6259 types), corresponding to 1245 speakers from 21 dialects of north american and british english, were analyzed ( ## results figure 2 shows the vowel plot for each dialect included in the study, with arrows reflecting the vowel trajectories for each of the five vowels. even from the empirical data, two findings are immediately clear: dialects are variable in their phonetic implementation of a given vowel, but there are also consistent patterns for the same vowel across dialects, including the anticipated monophthongdiphthong spectrum: from least movement for fleece to visible trajectories for choice, price, and mouth, with face showing dialect-specific variation consistent with monophthongal realization in scottish dialects (central scotland, edinburgh, glasgow, n. scotland & i) to diphthongs in other regions (east england, midwest us). again, the scottish dialects show a distinct fronting pattern for mouth (shown as a reduction in normalized f2) compared with other dialects where mouth typically shows a backing pattern as it raises. ## discussion this study has examined variability in english vowel realization across 21 dialects, to address the broad question of how to characterize variability in the 'same' vowel, across multiple acoustic dimensions, considering both static formant position and time-dependent dynamic information (trajectory shape, duration). what low-dimensional space does vowel variability lie in, does it line up with traditional notions of 'monophthong' vs. 'diphthong', and what role do static versus dynamic information play? our exploratory analysis (section 3.1) found that while dialects vary in the static and dynamic realization of vowels, this cross-dialectal variation is clearly structured: the 'same' vowel patterns similarly with respect to dynamic realization, across dialects. as a first approximation, the patterns of dynamic variation within vowels seems to broadly correspond to the general monophthong/diphthong characterization, related to varying degrees of formant 'movement' during the vowel timecourse: fleece exhibits the least change, followed by face, with price, mouth, choice showing the most change; duration patterns similarly. future work should incorporate more vowels into the analysis, to fully map out the structure of variability within and between dialects, and assess its possible sources. the dialect classification experiment (section 3.2) showed that whilst both formant position and trajectory shape can separately inform the prediction of a given dialect, accuracy is improved with both types of measures are used together. while previous work has shown that trajectory information is informative within a given dialect, these results demonstrate that characterizations of the formant trajectory also provide additional resolution as to the ways vowels can systematically differ across individual dialects. this study utilized one particular representation of trajectory shape: vector length/offset/angle. testing other representations of trajectory shape, such as dcts @xcite @xcite , would be a useful avenue for future research, especially if these improve on dialect classification accuracy, which is fairly low when using vector length/offset/angle. our understanding of cross-dialectal variation in vowel duration has been largely limited to studies of north american dialects, especially in the us south (e.g. @xcite @xcite , leaving open the question of how duration varies across english dialects more generally. results of the dialect classification experiment suggest that duration does contribute unique information over formant position and trajectory shape, but it is the least informative feature. however, this study only included vowels which are 'tense' in most dialects, which tend to be longer (than 'lax' vowels). future work incorporating more vowels into the analysis would allow for better assessment of the role of duration, and would provide additional information about about dialectal differences in duration across english vowels in general. to our knowledge, this is the largest study to date of formant dynamics (in terms of number of dialects, and tokens), for any language. analyzing data at this scale was made possible due to access to a large number of corpora and tools for automated acoustic measurement. previous large cross-dialectal analyses (e.g. @xcite @xcite were multi-year enterprises requiring substantial time and labor-intensive manual annotation, making only simple characterizations of vowel dynamics (e.g. onset + offset) possible. access to force-aligned speech corpora and the automatic measurement of formants allows the analysis to be 'scaled-up' easily relative to many other dialectal studies of vowel quality, but also requires recognition of a number of limitations for studies of this kind. whilst this method has been shown to generate accurate formant values and procedures are taken to avoid tracking 'false formants' @xcite , it is simply not possible with data at this scale to be manually validated. similarly forced aligned segments have a minimum time duration (often 30ms) and a minimum time resolution (often 10ms), particularly for vowels which may have undergone substantial reduction. we attempted to account for this by applying lower and upper-limits for vowel durations to be included in the study; it remains possible that biases or inaccuracies in vowel duration exist within the dataset.