How does Sinhala Machine Translation work?
- Rule-Based Machine Translation. This method relies on a set of linguistic rules and dictionaries to perform translations. It is effective for languages with well-defined grammar and syntax.
- Statistical Machine Translation. This approach uses statistical models derived from large corpora of bilingual text to predict translations based on probabilities. It adapts to various contexts by analyzing existing translations.
- Neural Machine Translation. This technique employs deep learning models to create end-to-end translation systems, allowing for more natural and fluid translations by understanding context better than traditional methods.
- Hybrid Machine Translation. This combines multiple translation methodologies, leveraging the advantages of each to improve the overall accuracy and fluency of translations in Sinhala.