德语阿尔卑斯地区方言语音的地理语言结构:使用众包数据的方言计量学方法

Pub Date : 2023-12-06 DOI:10.1515/opli-2022-0252
Philip C. Vergeiner, Lars Bülow
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引用次数: 0

摘要

阿尔卑斯地区因其保存完好的传统方言而在德语世界中脱颖而出,这些方言在日常生活中继续发挥着重要作用。然而,阿尔卑斯地区广阔的地理范围以及国家和地区边界的限制阻碍了对整个阿尔卑斯地区的全面调查。为了克服这些障碍,本研究利用来自 VerbaAlpina 项目的众包数据来调查德语阿尔卑斯地区的语音和形态-语音变异。虽然这些数据是以书面形式收集的,并且侧重于词汇变化,但研究表明,这些数据包含详细的语音信息。通过使用基于 19 个(形态)语音变量(包括 8,582 个词块)的多元方言计量(即因子分析 [FA]),该研究探索了阿尔卑斯地区德语方言的地理语言结构。研究结果从总体上证实了传统方言分类法的有效性。然而,研究结果也揭示了以前被低估的边界效应,尤其是沿德国-奥地利边界的巴伐利亚方言,这被认为是分化过程的结果。因此,该研究强调了从跨方言和跨国角度理解方言变异的重要性,并强调了众包数据在方言学研究中的价值。
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Geolinguistic structures of dialect phonology in the German-speaking Alpine region: A dialectometric approach using crowdsourcing data
The Alpine region stands out in the German-speaking world for its well-preserved traditional dialects, which continue to play a significant role in daily life. However, the vast geographical range of the Alpine region and the limitations imposed by national and regional borders have hindered comprehensive investigations of the entire Alpine area. To overcome these obstacles, this study utilizes crowdsourcing data from the VerbaAlpina project to investigate phonological and morpho-phonological variation in the German-speaking Alpine region. Although the data were collected in a written form and with a focus on lexical variation, it is shown that the data contain detailed phonological information. By using multivariate dialectometric measurements (i.e. factor analysis [FA]) based on 19 (morpho-)phonological variables (comprising 8,582 tokens), the study explores the geolinguistic structures of the German dialects in the Alpine region. The results confirm, on a general level, the validity of the traditionally established dialect classification. However, the findings also reveal previously underrated border effects, in particular for Bavarian dialects along the German-Austrian border, which are argued to be the outcome of divergence processes. Hence, the study highlights the importance of cross-dialectal and cross-national perspectives in understanding dialect variation and emphasizes the value of crowdsourcing data for dialectological research.
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