ELR-1000: A Community-Generated Dataset for Endangered Indic Indigenous Languages
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arXiv
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| Format: | Preprint |
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2025
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| author | Joshi, Neha Gogoi, Pamir Mirza, Aasim Jansari, Aayush Yadavalli, Aditya Pandey, Ayushi Shukla, Arunima Sudharsan, Deepthi Bali, Kalika Seshadri, Vivek |
| author_facet | Joshi, Neha Gogoi, Pamir Mirza, Aasim Jansari, Aayush Yadavalli, Aditya Pandey, Ayushi Shukla, Arunima Sudharsan, Deepthi Bali, Kalika Seshadri, Vivek |
| contents | We present a culturally-grounded multimodal dataset of 1,060 traditional recipes crowdsourced from rural communities across remote regions of Eastern India, spanning 10 endangered languages. These recipes, rich in linguistic and cultural nuance, were collected using a mobile interface designed for contributors with low digital literacy. Endangered Language Recipes (ELR)-1000 -- captures not only culinary practices but also the socio-cultural context embedded in indigenous food traditions. We evaluate the performance of several state-of-the-art large language models (LLMs) on translating these recipes into English and find the following: despite the models' capabilities, they struggle with low-resource, culturally-specific language. However, we observe that providing targeted context -- including background information about the languages, translation examples, and guidelines for cultural preservation -- leads to significant improvements in translation quality. Our results underscore the need for benchmarks that cater to underrepresented languages and domains to advance equitable and culturally-aware language technologies. As part of this work, we release the ELR-1000 dataset to the NLP community, hoping it motivates the development of language technologies for endangered languages. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_01077 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ELR-1000: A Community-Generated Dataset for Endangered Indic Indigenous Languages Joshi, Neha Gogoi, Pamir Mirza, Aasim Jansari, Aayush Yadavalli, Aditya Pandey, Ayushi Shukla, Arunima Sudharsan, Deepthi Bali, Kalika Seshadri, Vivek Computation and Language Human-Computer Interaction We present a culturally-grounded multimodal dataset of 1,060 traditional recipes crowdsourced from rural communities across remote regions of Eastern India, spanning 10 endangered languages. These recipes, rich in linguistic and cultural nuance, were collected using a mobile interface designed for contributors with low digital literacy. Endangered Language Recipes (ELR)-1000 -- captures not only culinary practices but also the socio-cultural context embedded in indigenous food traditions. We evaluate the performance of several state-of-the-art large language models (LLMs) on translating these recipes into English and find the following: despite the models' capabilities, they struggle with low-resource, culturally-specific language. However, we observe that providing targeted context -- including background information about the languages, translation examples, and guidelines for cultural preservation -- leads to significant improvements in translation quality. Our results underscore the need for benchmarks that cater to underrepresented languages and domains to advance equitable and culturally-aware language technologies. As part of this work, we release the ELR-1000 dataset to the NLP community, hoping it motivates the development of language technologies for endangered languages. |
| title | ELR-1000: A Community-Generated Dataset for Endangered Indic Indigenous Languages |
| topic | Computation and Language Human-Computer Interaction |
| url | https://arxiv.org/abs/2512.01077 |