What does "Simultaneous Machine Translation" mean?
Table of Contents
- How It Works
- The Role of Large Language Models
- Combining Strengths
- Progress in Simultaneous Translation
Simultaneous Machine Translation is a method where translations happen while the source text is still being read. This approach allows for quicker translation since it doesn't wait until the whole sentence is finished.
How It Works
A special system, often called a policy, decides the best time to read parts of the source text and translate them. Traditional methods mostly rely on specific models that do both the reading and translation at once. While these methods can decide well when to translate, they might not produce the best translations.
The Role of Large Language Models
Recent advances in technology have introduced Large Language Models (LLMs), which are powerful tools for generating text. These models are trained on vast amounts of information, which helps them produce high-quality translations. However, they often struggle with determining the best timing for translation under the simultaneous method.
Combining Strengths
New frameworks have been developed to combine the strengths of traditional methods and LLMs. In these systems, one agent decides the timing for translation, while another generates the actual translated text. This teamwork can lead to much better results in simultaneous translations.
Progress in Simultaneous Translation
Recent studies have shown that with minor adjustments, LLMs can effectively manage simultaneous translation tasks. By controlling how the input is segmented, these models can produce translations that are competitive with the best existing methods. There is also potential for closed-source models to work well in this area without needing prior training.