Conference paper Open Access

Multi-Task Modeling of Phonographic Languages: Translating Middle Egyptian Hieroglyphs

Philipp Wiesenbach; Stefan Riezler


JSON-LD (schema.org) Export

{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>Machine translation of ancient languages faces a low-resource problem, caused by the limited amount of available textual source data&nbsp;and their translations. We present a multi-task modeling approach to translating Middle Egyptian that is inspired by recent successful&nbsp;approaches to multi-task learning in end-to-end speech translation. We leverage the phonographic aspect of the hieroglyphic writing&nbsp;system, and show that similar to multi-task learning of speech recognition and translation, joint learning and sharing of structural&nbsp;information between hieroglyph transcriptions, translations, and POS tagging can improve direct translation of hieroglyphs by several&nbsp;BLEU points, using a minimal amount of manual transcriptions.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Computational Linguistics, Heidelberg University, Germany", 
      "@type": "Person", 
      "name": "Philipp Wiesenbach"
    }, 
    {
      "affiliation": "Computational Linguistics & IWR, Heidelberg University, Germany", 
      "@type": "Person", 
      "name": "Stefan Riezler"
    }
  ], 
  "headline": "Multi-Task Modeling of Phonographic Languages: Translating Middle Egyptian Hieroglyphs", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2019-11-02", 
  "url": "https://zenodo.org/record/3524924", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3524924", 
  "@id": "https://doi.org/10.5281/zenodo.3524924", 
  "@type": "ScholarlyArticle", 
  "name": "Multi-Task Modeling of Phonographic Languages: Translating Middle Egyptian Hieroglyphs"
}
69
42
views
downloads
All versions This version
Views 6969
Downloads 4242
Data volume 6.0 MB6.0 MB
Unique views 6060
Unique downloads 4141

Share

Cite as