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Purpose:This study examined the race identification of Southern American English speakers from two geographically distant regions in North Carolina. The purpose of this work is to explore how talkers' self-identified race, talker dialect region, and acoustic speech variables contribute to listener categorization of talker races. Method:Two groups of listeners heard a series of /h/–vowel–/d/ (/hVd/) words produced by Black and White talkers from East and West North Carolina, respectively. Results:Both Southern (North Carolina) and Midland (Indiana) listeners accurately categorized the race of all speakers with greater-than-chance accuracy; however, Western North Carolina Black talkers were categorized with the lowest accuracy, just above chance. Conclusions:The results suggest that similarities in the speech production patterns of West North Carolina Black and White talkers affect the racial categorization of Black, but not White talkers. The results are discussed with respect to the acoustic spectral features of the voices present in the sample population. 

Unfamiliar accents can cause word recognition challenges, particularly in noisy environments, but few studies have incorporated quantitative pronunciation distance metrics to explain intelligibility differences across accents. To address this gap, intelligibility was measured for 18 talkers -- two from each of three first-language, one bilingual, and five second-language accents -- in quiet and two noise conditions. The relations between two edit distance metrics, which quantify phonetic differences from a reference accent, and intelligibility scores were assessed. Intelligibility was quantified through both fuzzy string matching and percent words correct. Both edit distance metrics were significantly related to intelligibility scores; a heuristic edit distance metric was the best predictor of intelligibility for both scoring methods. Further, there were stronger effects of edit distance as the listening condition increased in difficulty. Talker accent also contributed substantially to intelligibility models, but relations between accent and edit distance did not consistently pattern for the two talkers representing each accent. Frequency of production differences in vowels and consonants was negatively correlated with intelligibility, particularly for consonants. Together, these results suggest that significant amounts of variability in intelligibility across accents can be predicted by phonetic differences from the listener’s home accent. However, talker- and accent-specific pronunciation features, including suprasegmental characteristics, must be quantified to fully explain intelligibility across talkers and listening conditions. 

Abstract Children exhibit preferences for familiar accents early in life. However, they frequently have more difficulty distinguishing between first language (L1) accents than second language (L2) accents in categorization tasks. Few studies have addressed children’s perception of accent strength, or the relation between accent strength and objective measures of pronunciation distance. To address these gaps, 6- and 12-year-olds and adults ranked talkers’ perceived distance from the local accent (i.e., Midland American English). Rankings were compared with objective distance measures. Acoustic and phonetic distance measures were significant predictors of ladder rankings, but there was no evidence that children and adults significantly differed in their sensitivity to accent strength. Levenshtein Distance, a phonetic distance metric, was the strongest predictor of perceptual rankings for both children and adults. As a percept, accent strength has critical implications for social judgments, which determine real world social outcomes for talkers with non-local accents. 

Listeners attend to variation in segmental and prosodic cues when judging accent strength. The relative contributions of these cues to perceptions of accentedness in English remains open for investigation, although objective accent distance measures (such as Levenshtein distance) appear to be reliable tools for predicting perceptual distance. Levenshtein distance, however, only accounts for phonemic information in the signal. The purpose of the current study was to examine the relative contributions of phonemic (Levenshtein) and holistic acoustic (dynamic time warping) distances from the local accent to listeners’ accent rankings for nine non-local native and nonnative accents. Listeners (n =52) ranked talkers on perceived distance from the local accent (Midland American English) using a ladder task for three sentence-length stimuli. Phonemic and holistic acoustic distances between Midland American English and the other accents were quantified using both weighted and unweighted Levenshtein distance measures, and dynamic time warping (DTW). Results reveal that all three metrics contribute to perceived accent distance, with the weighted Levenshtein slightly outperforming the other measures. Moreover, the relative contribution of phonemic and holistic acoustic cues was driven by the speaker’s accent. Both nonnative and non-local native accents were included in this study, and the benefits of considering both of these accent groups in studying phonemic and acoustic cues used by listeners is discussed. 

Abstract Online testing for behavioral research has become an increasingly used tool. Although more researchers have been using online data collection methods, few studies have assessed the replicability of findings for speech intelligibility tasks. Here we assess intelligibility in quiet and two noise-added conditions for several different accents of English (Midland American, Standard Southern British, Scottish, German-accented, Mandarin-accented, Japanese-accented, and Hindi-English bilingual). Participants were tested in person at a museum-based laboratory and online. Results showed little to no difference between the two settings for the easier noise condition and in quiet, but large performance differences in the most difficult noise condition with an advantage for the participants tested online. Technology-based variables did not appear to drive the setting effect, but experimenter presence may have influenced response strategy for the in-person group and differences in demographics could have provided advantages for the online group. Additional research should continue to investigate how setting, demographic factors, experimenter presence, and motivational factors interact to determine performance in speech perception experiments.