Temporal variability in four Alemannic dialects and its influence on the respective varieties of Swiss Standard German

Abstract

Languages, dialects, and speakers have been found to show variability in articulation rate and speech rhythm. The present study examines whether temporal variability found between four Alemannic (ALM) dialects is also present in the same speakers' Swiss Standard German (SSG) varieties. The results suggest that ALM interferences are not systematic. Whereas in ALM dialects, Churspeakers show the quickest articulation rate and Brig speakers the slowest, amongst the SSG varieties, Zurich speakers articulated the most quickly and Bern the most slowly. As for further rhythm metrics, the insights of this study provide evidence that consonantal variability is more telling regarding dialect/variety identification than vocalic measures.

Investigating speaker individuality in the Swiss Standard German of four Alemannic dialect regions: Consonant quantity, vowel quality, and temporal variables

“…When we look at temporal variables, things become a bit complicated. While previous research has found that ALM dialects differ statistically significantly regarding rhythmic measurements (Leemann et al, 2012;2014a;2014b;2018), this was not confirmed for SSG (Zihlmann, 2020b). What is more, on the speaker level, already Dellwo et al's (2015) study showed that interspeaker variation amongst ALM speakers is rather great, which has also been found in this study for both ALM and SSG regardless of their dialect background.…”

“…On top of this, regarding the evidence that some temporal measurements stay stable when speaking a foreign language (de Jong, 2018;de Jong & Mora, 2019), this could not be confirmed for ALM and SSG articulation rates (AR) and the share of vocalic speech in percent (%V) as only 2 and 4 speakers, respectively, showed similar values in the 2 varieties. On average, neither AR nor %V showed statistically significant region-specific values in SSG (Zihlmann, 2020b). Furthermore, the speaker-specific evaluation reveals that some speakers even show more similarities with speakers of other dialects than with speakers of their own one, as it is the case for, e.g., the AR of BE01 and BE02 that are much more similar with the ones of VS01, GR09 or ZH08 than with the ones of BE03 or BE06.…”

“…This could prove to be insightful as studies have shown individual speech styles to be stable between a speaker's native and foreign language (see de Jong, 2018;de Jong & Mora, 2019). Zihlmann (2020b) thus analysed region-specific rhythmic variability in ALM and SSG, verifying whether the temporal characteristics of ALM dialects stay stable when the same speakers switch to SSG. The analysis was based on a further examination of the stimuli used for Zihlmann's (2020a) study.…”

“…To shed more light on regional SSG differences, this study will examine Zihlmann's (2020b) results on the speaker level. The focus will lie on speaker individuality in AR and %V, which turned out to be good indicators to for interspeaker variation in several languages, even though they did not show statistically significant interdialectal differences in Zihlmann's (2020b) study.…”

“…By focusing on the phonetic level, this study explores speaker individuality in spoken SSG while keeping in mind the ALM dialect situation in Switzerland. The corpora used for the analysis consist of data collected for three previous studies that assessed dialect-specific ALM influences on SSG vowel and consonant quantity (Zihlmann, 2020a), SSG vowel quality (Zihlmann, 2021), and SSG temporal features (Zihlmann, 2020b). As in all studies intradialectal interspeaker variation had been observed, the current study will deal with speaker individuality in three features that showed statistically significant interdialectal differences.…”