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🚀 Indigenous Language Translator Engine (ILTE) v3.0.0-Alpha.3 Release 🎉
🌟 Introducing ILTE-ATI v3.0.0-Alpha.3 – A Next-Gen Iterative Translation Engine
The Indigenous Language Translator Engine (ILTE) v3.0.0-Alpha.3 introduces ILTE-ATI (Iterative Translation Engine), the most advanced version yet, with attention-based iterative translation, multi-stage candidate refinement, and dynamic normalization.
This release includes:
- 🌱 ILTE-ALT v2.1.0-Beta.2 – Lightweight dictionary-based translation engine.
- 🧐 ILTE-ADV v2.1.1-Alpha.2 – AI-driven, context-aware translation engine.
- 🧠 ILTE-ZS v2.1.2-Beta.3 – Hybrid, resource-efficient translation engine with RBMT, FST, semantic matching, and zero-shot capabilities.
- ✨ ILTE-ATI v3.0.0-Alpha.3 (NEW!) – The most advanced iterative and attention-based translation engine with multi-pass processing and enhanced contextual awareness.
🚨 This is an Alpha release. Further refinements and optimizations will follow. 🚨
🔄 What's New in v3.0.0?
✨ ILTE-ATI v3.0.0-Alpha.3 (Iterative Translation Engine with Attention Mechanism)
- 🏆 Attention-Based Context Window
- Wider sentence analysis ensures better context comprehension.
- Dynamically adapts to sentence structure for more accurate translations.
- 🌀 Iterative Multi-Pass Translation for Refinement
- Each translation cycle improves on the last for enhanced accuracy.
- Prevents misinterpretations by checking and refining in multiple iterations.
- 🔍 Enhanced Word Candidate Selection
- Uses similarity-based ranking to determine best word choices.
- Dynamically selects alternative phrases when necessary.
- ⚡ Optimized Performance & Resource Handling
- Improved multi-threading & multi-processing for faster execution.
- Better cache management to avoid redundant processing.
- 📊 Detailed Report Generation
- DOCX report now includes:
- Confidence scores, refinement passes, and method breakdowns.
- Preserved document formatting (paragraphs, indentations, and spacing).
- DOCX report now includes:
📊 ILTE-ATI vs. ILTE-ZS vs. ILTE-ALT vs. ILTE-ADV
| Feature | ILTE-ALT 🌱 | ILTE-ZS 🧠 | ILTE-ADV 🧐 | ILTE-ATI ✨ |
|---|---|---|---|---|
| Translation Approach | Dictionary-Based | Dictionary + RBMT + FST + Semantic + Zero-Shot | Dictionary + Semantic + Context-Based AI | Attention-Based + Iterative Multi-Pass |
| Processing Speed | Fast | Optimized | Slower | Balanced, Optimized for Accuracy |
| Handling Large Files | Struggles | Efficient Chunking | Slower | Optimized Chunking & Iterative Processing |
| Memory Usage | Low | Moderate | High | Balanced, Adaptive Resource Usage |
| Context Awareness | None | Partial | Strong | 🏆 Very Strong (Multi-Pass Context Analysis) |
| Idiomatic Expressions | Limited | Rule-Based (RBMT) | AI-Based | AI-Based + Refinement Mechanism |
| Parallelization | Minimal | Thread + Process Pool | DataLoader-Based | Multi-Process + Thread Optimization |
| Zero-Shot Capability | No | Yes | Yes | Yes (Adaptive Candidate Selection) |
| Best Use Case | Fast, simple translation | Large text processing | High-accuracy, AI-based translation | High-Precision, Context-Aware, Adaptive Translation |
🎯 ILTE-ATI v3.0.0 Translation Flow Breakdown
1️⃣ Advanced Preprocessing
- Text normalization using hierarchical rules (Unicode cleanup, stemming, and regex-based tokenization).
- Sentence restructuring to improve translation context.
- Broad context windowing for improved sentence understanding.
2️⃣ Multi-Stage Translation Pipeline
- Dictionary Lookup → RBMT & FST Transformation → Contextual Semantic Matching → Adaptive Candidate Selection.
- Iterative refinement cycles for self-correcting translation passes.
- Parallel execution for optimal speed and efficiency.
3️⃣ Confidence Scoring & Adaptive Candidate Refinement
- Assigns dynamic confidence scores based on:
- Translation method (Dictionary, Semantic, RBMT, FST, Attention-Based, etc.).
- Word position within a sentence and its surrounding context.
- Iterates until an optimal translation is reached.
4️⃣ Final Output & Report Generation
- Outputs structured translation results with full formatting preservation.
- DOCX report includes:
- Translation accuracy scores, processing time, and method logs.
- Iterative refinement breakdown to track improvement over cycles.
🌐 Installation & Usage
Installing Dependencies
pip install -r requirements.txtRunning ILTE-ATI v3.0.0 (Iterative Attention Engine)
python engine_ATI.pySelecting Input Type
👉 Manual Input: Enter text directly.
👉 File Upload: Provide a document for batch processing.
🛠️ System Requirements
ILTE-ATI v3.0.0 (Iterative Attention Engine)
- CPU: Intel Core i7 / AMD Ryzen 7 or higher.
- RAM: 16GB+ (32GB Recommended for Large Translations).
- Storage: 2GB+ free space.
- Python: 3.10+.
- GPU Acceleration Highly Recommended (Supports CUDA for PyTorch models).
🌟 Future Plans & Improvements
- ✅ Further Optimizing Attention Mechanisms for better handling of complex sentences.
- ✅ Fine-Tuning Multi-Pass Translation Logic for iterative refinements.
- ✅ Expanding contextual understanding through ML-driven linguistic models.
- ✅ Lowering computation time without reducing accuracy.
📚 License & Contribution
- Licensed under GPL v3 – Open Source & Community Driven! 🌍
- Contribute & Improve – Join us in preserving indigenous languages! 🌱
🏆 Developed by XI TJKT 2 Development Team 🧑💻