How does Armenian Machine Translation work?
- Statistical Machine Translation (SMT). This method relies on statistical models to predict the likelihood of a sequence of words being valid, improving translation by learning from large datasets.
- Neural Machine Translation (NMT). NMT uses deep learning models to improve the contextual understanding of languages, resulting in more fluent and accurate translations.
- Rule-based Machine Translation (RBMT). RBMT utilizes predefined linguistic rules and dictionaries, which allows for a highly specialized translation process, especially for fixed language pairs.
- Hybrid Machine Translation. This approach combines multiple translation methods, leveraging the strengths of each to provide more accurate translations across different contexts.