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First English-Syriac machine translation model developed for endangered language

By PulseAugur Editorial · [1 sources] ·

Researchers have developed the first phrase-based Statistical Machine Translation (SMT) model for English-to-Syriac translation, addressing the language's status as endangered and understudied in Natural Language Processing (NLP). The study created a dataset of nearly 40,000 sentence pairs from the English and Syriac Bible, employing custom scripts for data extraction and manual alignment. The best-performing model achieved a BLEU score of 23.54, with human evaluations showing adequate and fluent translations. This work provides a publicly available dataset and a baseline for future NLP research on Syriac. AI

IMPACT Provides a foundational dataset and model for NLP research on endangered languages, potentially enabling new applications.

RANK_REASON Academic paper detailing a new machine translation model and dataset for a low-resource language. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

First English-Syriac machine translation model developed for endangered language

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Academic paper detailing a new machine translation model and dataset for a low-resource language. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Hadiana Sliwa, Hossein Hassani ·

    Machine Translation between English and Syriac (East Syriac Dialect) using Statistical Machine Learning

    arXiv:2609.18529v1 Announce Type: new Abstract: UNESCO considers the Assyrian (Syriac) language an endangered language. Although Assyrians speak the language worldwide, the speaking population is uncertain (ranging from 500,000 to 1,500,000). Syriac is also one of the least studi…

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