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The Perso-Arabic scripts are a family of scripts that are widely adopted andused by various linguistic communities around the globe. Identifying variouslanguages using such scripts is crucial to language technologies andchallenging in low-resource setups. As such, this paper sheds light on thechallenges of detecting languages using Perso-Arabic scripts, especially inbilingual communities where ``unconventional'' writing is practiced. To addressthis, we use a set of supervised techniques to classify sentences into theirlanguages. Building on these, we also propose a hierarchical model that targetsclusters of languages that are more often confused by the classifiers. Ourexperiment results indicate the effectiveness of our solutions.

PALI: A Language Identification Benchmark for Perso-Arabic Scripts