How does Somali Machine Translation work?
- Statistical Machine Translation. This method uses statistical models based on the analysis of parallel corpora to infer relationships between source and target languages.
- Neural Machine Translation. Utilizing deep learning techniques, this approach leverages neural networks to enhance the quality and fluency of translations by analyzing entire sentences as a context.
- Rule-Based Translation. This traditional method relies on predefined linguistic rules and linguistic knowledge to translate text, allowing for precise control over the output.
- Transformer Models. This modern approach employs transformer architectures to allow for more efficient processing of long-range dependencies in text, significantly improving translation results.