使用监督机器学习模型识别美国芬兰语使用者的方言背景

IF 0.5 3区 文学 0 LANGUAGE & LINGUISTICS
I. Ivaska, Mirva Johnson, Tommi Kurki
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引用次数: 0

摘要

本研究介绍了两个实验的结果,使用监督机器学习模型来检查芬兰语使用者的方言背景。数据来自对威斯康星州北部芬兰语传统使用者的采访,并与芬兰方言语法档案中的数据进行了比较。构建了这些模型,然后在成功的验证测试后,用于识别五位美国-芬兰语使用者的方言背景。结果表明,方言背景的个体差异与说话人可能的语言输入存在一定的相关性。我们的方法提供了一种新的方法论工具,用于在语言接触的情况下考察说话者的方言背景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying the dialectal background of American Finnish speakers using a supervised machine-learning model
This study presents results of two experiments using supervised machine-learning models to examine individual Finnish speakers’ dialectal backgrounds. Data come from interviews conducted with heritage speakers of Finnish in northern Wisconsin and are compared to data from the Finnish Dialect Syntax Archive. The models were constructed and then, following successful validation testing, used to identify the dialectal background of five individual American Finnish speakers. Results showed individual variation in dialectal backgrounds and some correlation to speakers’ likely language input. Our approach offers a new methodological tool for examining speakers’ dialectal backgrounds in situations of language contact.
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来源期刊
CiteScore
1.20
自引率
20.00%
发文量
22
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