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New multilingual corpus AlphaMWE targets machine translation challenges

By PulseAugur Editorial · [1 sources] ·

Researchers have developed AlphaMWE, a multilingual parallel corpus designed to aid research in machine translation and lexicography. This corpus includes annotations for multi-word expressions (MWEs) across six languages: Arabic, Chinese, English, German, Italian, and Polish. The creation process involved machine translation followed by human post-editing and annotation, with a focus on ensuring high quality through multiple review stages. A key finding from this work is that accurately translating MWEs remains a significant challenge for current state-of-the-art machine translation systems. AI

IMPACT This corpus could improve machine translation systems' ability to handle complex linguistic structures like multi-word expressions.

RANK_REASON This is a research paper describing the creation of a new dataset for NLP research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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

New multilingual corpus AlphaMWE targets machine translation challenges

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This is a research paper describing the creation of a new dataset for NLP research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Lifeng Han, Najet Hadj Mohamed, Malak Rassem, Gareth Jones, Alan Smeaton, Goran Nenadic ·

    Towards a resource for multilingual lexicons: an MT assisted and human-in-the-loop multilingual parallel corpus with multi-word expression annotation

    arXiv:2011.03783v3 Announce Type: replace-cross Abstract: In this work, we introduce the construction of a machine translation (MT) assisted and human-in-the-loop multilingual parallel corpus with annotations of multi-word expressions (MWEs), named AlphaMWE. The MWEs include verb…

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