The Romansh language has several regional varieties, called idioms, which sometimes have limited mutual intelligibility. Despite this linguistic diversity, there has been a lack of documented efforts to build a language identification (LID) system that can distinguish between these idioms. Since Romansh LID should also be able to recognize Rumantsch Grischun, a supra-regional variety that combines elements of several idioms, this makes for a novel and interesting classification problem. In this paper, we present a LID system for Romansh idioms based on an SVM approach. We evaluate our model on a newly curated benchmark across two domains and find that it reaches an average in-domain accuracy of 97%, enabling applications such as idiom-aware spell checking or machine translation. Our classifier is publicly available.

翻译：罗曼什语包含多种区域变体（称为习语），这些变体之间有时互通性有限。尽管存在这种语言多样性，但目前尚未有文献记载构建能够区分这些习语的语言识别（LID）系统的相关努力。由于罗曼什语LID还需能够识别结合了多种习语元素的跨区域变体“罗曼什统一语”（Rumantsch Grischun），这构成了一个新颖且有趣的分类问题。本文提出了一种基于支持向量机（SVM）方法的罗曼什习语LID系统。我们在新整理的两个领域基准数据集上评估了该模型，发现其平均领域内准确率达到97%，从而支持了诸如习语感知拼写检查或机器翻译等应用。该分类器已公开发布。