How does Korean Machine Translation work?
- Statistical Machine Translation. This method uses statistical models to translate by analyzing large corpora of bilingual texts to learn patterns and probabilities between languages.
- Neural Machine Translation. Neural networks are used in this method to allow for more contextually aware translations, enabling better handling of idioms and complex sentence structures.
- Rule-based Machine Translation. This approach relies on a set of linguistic rules and dictionaries created by experts, focusing on grammatical and semantic analysis of the source text.
- Hybrid Machine Translation. Combining various approaches, hybrid systems utilize the strengths of both statistical and rule-based methods for improved accuracy and fluency in translations.