As Artificial Intelligence is becoming an integral part of everything, machine translation is gaining popularity these days. Since more companies are now moving towards adoption of machine translation for their high-volume content, there is a rising need to assess these translations in order to ensure they are accurate and linguistically valid.
Even with advanced machine translation tools in practice, companies still rely on trained and expert linguists to achieve the desired translation quality. Machine Translation Post Editing (MTPE) combines the speed and efficiency of machine translation with the accuracy and expertise of human linguists.
However, achieving quality MTPE for your company translations is a tough endeavor in itself. Here are some best practices to achieve global success through MTPE services.
MTPE Best Practices
If you have opted to use machine translation services along with post-editing for your content, there are few essential best practices that you must keep in consideration.
Start off with source text
Just like all translation projects created by a professional translation company, the source text should be created first as well as pre-edited. Pre-editing a source text ensures that both the post-editors as well as the MT engines are working on the accurate text. In addition, early errors can create problems in the whole translation project. This is the reason why source text should be carefully scrutinized, and assessed for any grammatical or expression errors to prepare it for editing by machine translation. This means that editing sentence structures, date formats, and sentence lengths are a must so that machine translation can pick the text up.
Build your post-editing strategy
In MTPE services, the foremost thing to consider is opting for a post-editing strategy that will produce the most accurate and professional outcome. Although the amount of post-editing requirements varies from project to project, it is essential to define priorities from the start. The three main considerations for post-editing are time, cost, and quality. According to these considerations, there are three main strategies that you can adopt:
1. Light post-editing
Just like its name, light post-editing involves modification of raw MT only where it is absolutely necessary. This is to ensure that the output by machine translation services is legible and has the meaning of the source document intact. In light post-editing, the editor should aim for making as few changes as possible. This approach results in fast and cost-effective results.
2. Project-specific editing
Every translation project holds different requirements that a professional translation company is expected to understand to the best of its expertise. Editors must choose projects that give them the edge on time, cost, and desired quality. Also, it may pay off to choose the project that has a higher business value than others. One other option is that companies can choose not to use post-editing at all. Such an approach can work best for internal documents where the output of machine translation is expected. Additionally, these work best where there is little risk of bad translations going wrong.
3. Full-post editing
In contrast to light post-editing, full-post editing involves a complete modification and review of the raw text to make sure there are no errors. Light-post editing is concerned with achieving slight accuracy and legibility. On the other hand, full-post editing involves a consideration of a number of factors such as style and tone consistency. It also includes a removal of all grammatical errors, adjustments of cultural elements, and fixing of idiomatic expressions. A complete overhaul of the document ensures high accuracy and quality. Although this approach is slower and expensive, it produces a highly accurate output.
Choose your MT engine
Choosing the right machine translation engine can make a big impact on the quality of post editing services. As time and costs are the deciding factors for choosing an MT engine, it is critical to choose one that leads to reduction in both.
Generally speaking, neural machine engines outperform statistical and rule-based engines, depending on the content and target languages of the project. The choice of machine translation engine will also depend on which languages you are planning to translate into. This is because some MT engines work best with European languages. Others specialize in giving optimal output for Asian languages.
Select your Post-Editing Partner carefully
Just like the choice of a machine translation engine can have a big impact on the quality of your translation project, choosing the right translation partner is also essential. To choose the right post-editing services partner, you first need to define your priorities. Do you wish to appoint a translation agency for your project? Or do you plan to appoint an independent post-editor? After that, you need to choose a translation partner that has more experience, greater translation expertise and affordable rates. Additionally, a portfolio of high-quality projects is a must too. Most importantly, your chosen translation partner must be aware of your industry terminology and should be fluent in both the source and target languages.
Conclusion
Machine translation is a need of many translation companies in recent times, considering the complexity of projects. However, machine translation output needs to be tested and assessed to eliminate any errors and mistakes. Machine translation post-editing ensures all errors in the content are removed and the text is ready for globalizing without any hassle.
read more articles visit webvk.in