metadata

title: Siswati-English Linguistic Translation Tool
emoji: 🔬
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.33.2
app_file: app.py
pinned: false
license: apache-2.0
tags:
  - translation
  - siswati
  - linguistics
  - african-languages
  - nlp
  - research
  - corpus-analysis
  - bantu-languages
  - m2m100
  - multilingual

🔬 Siswati-English Linguistic Translation Tool

An advanced AI-powered translation system with comprehensive linguistic analysis features, designed specifically for linguists, researchers, and language documentation projects working with Siswati and English.

🌟 Features

🔄 Translation Capabilities

Bidirectional Translation: High-quality English ↔ Siswati translation
Advanced Model Architecture: Built on M2M100 transformer models
Batch Processing: Process multiple texts simultaneously for corpus analysis
Real-time Analysis: Instant linguistic metrics and feature detection

📊 Linguistic Analysis

Morphological Complexity: Word length, sentence structure analysis
Lexical Diversity: Vocabulary richness measurements
Language-Specific Features: Siswati agglutination, click consonants, tone markers
Translation Ratios: Comparative analysis between source and target languages
Statistical Metrics: Character count, word count, sentence segmentation

🔬 Research Tools

Translation History: Track and analyze translation patterns over time
CSV Export: Research-ready data export for statistical analysis
Corpus Management: Batch processing for linguistic corpora
Performance Metrics: Processing time and efficiency tracking

🗣️ About Siswati

Siswati (also known as Swati or Swazi) is a Bantu language spoken by approximately 2.3 million people, primarily in:

🇸🇿 Eswatini (Kingdom of Eswatini) - Official language
🇿🇦 South Africa - One of 11 official languages

Linguistic Features

Language Family: Niger-Congo → Bantu → Southeast Bantu
Script: Latin alphabet
Characteristics: Agglutinative morphology, click consonants, tonal
ISO Code: ss (ISO 639-1), ssw (ISO 639-3)

🤖 Model Information

This tool uses state-of-the-art transformer models developed by the Data Science for Social Impact Research Group:

English → Siswati: dsfsi/en-ss-m2m100-combo
Siswati → English: dsfsi/ss-en-m2m100-combo

Both models are based on Meta's M2M100 architecture, fine-tuned specifically for Siswati-English translation pairs.

🎯 Use Cases

For Linguists & Researchers

Language Documentation: Analyze translation patterns and linguistic features
Corpus Studies: Process large text collections with batch translation
Comparative Analysis: Study morphological and syntactic differences
Quality Assessment: Evaluate translation adequacy and fluency

For Educators & Students

Language Learning: Understand translation patterns and linguistic structures
Academic Research: Export data for statistical analysis and publications
Computational Linguistics: Study machine translation for low-resource languages

For Community & Cultural Projects

Language Preservation: Support Siswati language documentation efforts
Cultural Exchange: Facilitate communication between English and Siswati speakers
Content Translation: Assist in translating educational and cultural materials

🚀 Getting Started

Single Translation: Enter text and select translation direction
Batch Processing: Upload .txt files or paste multiple lines for corpus analysis
Analysis Export: Use the research tools to export translation data as CSV
Linguistic Study: Explore the real-time analysis features for detailed insights

📈 Linguistic Metrics Explained

Text Complexity

Word Count: Total number of words in the text
Character Count: Total characters including spaces and punctuation
Sentence Count: Number of sentences detected
Average Word Length: Mean character length per word
Lexical Diversity: Ratio of unique words to total words (vocabulary richness)

Translation Analysis

Word Ratio: Target word count / Source word count
Character Ratio: Target character count / Source character count
Processing Time: Time taken for model inference

Siswati-Specific Features

Agglutination Detection: Identification of potentially agglutinated words (>10 characters)
Click Consonants: Count of clicks (c, q, x sounds)
Tone Markers: Detection of acute (́) and grave (̀) accent marks

📚 Academic Usage

If you use this tool in your research, please cite the original models:

@misc{dsfsi-siswati-translation,
  title={Siswati-English Translation Models},
  author={Marivate, Vukosi and Lastrucci, Richard},
  year={2024},
  publisher={Data Science for Social Impact Research Group},
  url={https://github.com/dsfsi/}
}

🔗 Related Resources

Model Repositories: En-Ss Model | Ss-En Model
Research Group: DSFSI
Feedback: Research Feedback Form

🤝 Contributing

We welcome contributions from the linguistic and NLP communities! Areas of interest:

Improving translation quality
Adding more linguistic analysis features
Expanding to other African languages
Enhancing the user interface for research workflows

📄 License

This project is licensed under the Apache 2.0 License. The underlying models may have their own licensing terms - please check the individual model repositories.

🌍 Supporting African Languages

This tool is part of a broader effort to support African language technology and computational linguistics research. By providing advanced NLP tools for Siswati, we aim to:

Preserve and promote African languages in the digital age
Support linguistic research and documentation
Enable better communication across language barriers
Contribute to the development of multilingual AI systems

Built with ❤️ for the African NLP community