GRC - Alignment: An Open - Source Multilingual Word - Level Text Alignment Model - Free for Text Alignment between Ancient Greek and Other Languages

Grc Alignment

Developed by UGARIT

A multilingual word-level text alignment model based on XLM-RoBERTa architecture, specifically optimized for Ancient Greek text alignment tasks with other languages

Machine Translation

Transformers

#Ancient Greek Text Alignment #Multilingual Word-Level Alignment #Classical Text Processing

Downloads 48

Release Time : 5/7/2022

Model Overview

This model achieves word-level text alignment between Ancient Greek and multiple languages (English, Latin, Georgian, etc.) through pre-training and fine-tuning, suitable for classical literature research and translation alignment tasks

Model Features

Multilingual Alignment Capability

Supports word-level alignment between Ancient Greek and multiple languages including English, Latin, and Georgian

Domain-Specific Optimization

Pre-trained on 12 million monolingual Ancient Greek words and optimized for classical text characteristics

High-Quality Training Data

Fine-tuned using 45,000 parallel sentences from authoritative sources like the Perseus Digital Library

Model Capabilities

Ancient Greek-English Text Alignment

Ancient Greek-Latin Text Alignment

Ancient Greek-Georgian Text Alignment

Cross-Language Word-Level Alignment

Classical Literature Translation Alignment

Use Cases

Classical Literature Research

Homeric Epic Alignment Analysis

Word-level alignment between Ancient Greek originals and English translations of 'Iliad' and 'Odyssey'

Alignment error rate 19.73% (GRC-ENG)

Historical Text Cross-Language Comparison

Alignment analysis of Ancient Greek historians' works with Latin translations

Alignment error rate 10.60% (GRC-LAT)

Digital Humanities Tools

Translation Alignment Editor Integration

Provides automatic alignment functionality for UGARIT Translation Alignment Editor

Supports 5 language combinations

🚀 Automatic Translation Alignment of Ancient Greek Texts

The GRC-ALIGNMENT model is an XLM-RoBERTa-based model, fine-tuned for automatic multilingual text alignment at the word level. It is trained on 12 million monolingual ancient Greek tokens with the Masked Language Model (MLM) training objective. Additionally, the model is fine-tuned on 45k parallel sentences, mainly in ancient Greek-English, Greek-Latin, and Greek-Georgian.

✨ Features

Multilingual Training: The model is trained on multiple language pairs, including ancient Greek-English, Greek-Latin, and Greek-Georgian, enabling it to perform well in various multilingual alignment tasks.
Word-Level Alignment: It can achieve automatic multilingual text alignment at the word level, providing more accurate alignment results.

📦 Installation

No installation steps are provided in the original document, so this section is skipped.

📚 Documentation

Multilingual Training Dataset

Property	Details
Languages and Sentences	GRC-ENG: 32,500 sentences from Perseus Digital Library (Iliad, Odyssey, Xenophon, New Testament) GRC-LAT: 8,200 sentences from Digital Fragmenta Historicorum Graecorum project GRC-KAT, GRC-ENG, GRC-LAT, GRC-ITA, GRC-POR: 4,000 sentences from UGARIT Translation Alignment Editor

Model Performance

Property	Details
Alignment Error Rates	GRC-ENG: 19.73% (IterMax) GRC-POR: 23.91% (IterMax) GRC-LAT: 10.60% (ArgMax)

The gold standard datasets are available on Github.

📄 License

This project is licensed under the CC BY 4.0 license.

If you use this model, please cite our papers:

@InProceedings{yousef-EtAl:2022:LREC,
  author    = {Yousef, Tariq  and  Palladino, Chiara  and  Shamsian, Farnoosh  and  dâ€™Orange Ferreira, Anise  and  Ferreira dos Reis, Michel},
  title     = {An automatic model and Gold Standard for translation alignment of Ancient Greek},
  booktitle      = {Proceedings of the Language Resources and Evaluation Conference},
  month          = {June},
  year           = {2022},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {5894--5905},
  url       = {https://aclanthology.org/2022.lrec-1.634}
}

@InProceedings{yousef-EtAl:2022:LT4HALA2022,
  author    = {Yousef, Tariq  and  Palladino, Chiara  and  Wright, David J.  and  Berti, Monica},
  title     = {Automatic Translation Alignment for Ancient Greek and Latin},
  booktitle      = {Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages},
  month          = {June},
  year           = {2022},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {101--107},
  url       = {https://aclanthology.org/2022.lt4hala2022-1.14}
}

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