2021
DOI: 10.48550/arxiv.2103.11401
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SwissDial: Parallel Multidialectal Corpus of Spoken Swiss German

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“…Despite being a more delicate task, spoken dialect identification received comparatively lower attention, most of it being devoted to dialect identification for widely spoken languages, such as English [8], Chinese [9], and Arabic [10,11,12]. Spoken dialect identification for low-resource languages, such as Swiss German [13,14] and Finnish [15], has remained relatively underexplored. Different from prior studies, we focus on spoken language identification in Romanian, a low-resource language characterized by its intricate dialectal variations within the country of Romania.…”
Section: Introductionmentioning
confidence: 99%
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“…Despite being a more delicate task, spoken dialect identification received comparatively lower attention, most of it being devoted to dialect identification for widely spoken languages, such as English [8], Chinese [9], and Arabic [10,11,12]. Spoken dialect identification for low-resource languages, such as Swiss German [13,14] and Finnish [15], has remained relatively underexplored. Different from prior studies, we focus on spoken language identification in Romanian, a low-resource language characterized by its intricate dialectal variations within the country of Romania.…”
Section: Introductionmentioning
confidence: 99%
“…This has led to a growing need for resources on low-resource languages. Considering dialect identification datasets across different languages, we can distinguish between two types of resources: text-based datasets [20,21,22,23,24] and speechbased datasets [10,11,12,13,14,15]. While various languages have benefited from text-based resources that leverage written materials capturing linguistic variations, the auditory dimension of dialects adds an intricate layer of complexity.…”
Section: Introductionmentioning
confidence: 99%
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