Constructing and Expanding Low-Resource and Underrepresented Parallel Datasets for Indonesian Local Languages

arXiv:2404.01009v1 Announce Type: new
Abstract: In Indonesia, local languages play an integral role in the culture. However, the available Indonesian language resources still fall into the category of limited data in the Natural Language Processing (NLP) field. This is become problematic when build NLP model for these languages. To address this gap, we introduce Bhinneka Korpus, a multilingual parallel corpus featuring five Indonesian local languages. Our goal is to enhance access and utilization of these resources, extending their reach within …

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