Listeners are able to quite accurately distinguish between different dialects of their native language, but little is known about the process of dialect identification and the phonetic cues listeners use to identify someone's regional origin. This study examines how different segments, acoustic between-dialect distance, and the listeners' knowledge about a dialect contribute to this process. Native speakers of Grison and Zurich German were asked to categorize isolated words spoken by eight speakers of Grison and eight speakers of Zurich German. Stimuli (...) contained either none, one, or two segmental cues to regional origin. The presence of one dialect-specific segment was enough to allow for an identification rate well above chance. Sensitivity measures and analysis of reaction time showed that the two dialect groups largely relied on the same segmental cues. Acoustic distance to the other dialect, quantified as Euclidean distance in the F1×F2 vowel space, generally facilitated dialect identification, but interacted with native speakers' general knowledge about the dialects: In segments which listeners explicitly associate with one of the two dialects, acoustic distance facilitated dialect recognition to a larger extent than in segments listeners are not aware of dialectal variation. The results suggest that, depending on the prior knowledge about a dialect, acoustic variation is weighted differently. Further analysis showed that Zurich listeners were more sensitive to the dialect differences, responded faster, and presented a more-marked own-dialect response bias than Grison listeners. These findings are in line with the status of Grison German as a marked and Zurich German as a neutral dialect and suggest that, depending on their own dialect's status, listeners used different decision strategies. (shrink)

We investigated the emergence of sociolinguistic indexicality using an artificial-language-learning paradigm. Sociolinguistic indexicality involves the association of linguistic variants with nonlinguistic social or contextual features. Any linguistic variant can acquire “constellations” of such indexical meanings, though they also exhibit an ordering, with first-order indices associated with particular speaker groups and higher-order indices targeting stereotypical attributes of those speakers. Much natural-language research has been conducted on this phenomenon, but little experimental work has focused on how indexicality emerges. Here, we present three (...) miniature artificial-language experiments designed to break ground on this question. Results show ready formation of first-order indexicality based on co-occurrence alone, with higher-order indexicality emerging as a result of extension to new speaker groups, modulated by the perceived practical importance of the indexed social feature. (shrink)