Machine Translation Post Editing, or MTPE, represents the intersection of machine-generated translation and human expertise. It involves the careful assessment and correction of texts translated by automated systems, leveraging human understanding to bring coherence, accuracy, and nuance. This is vital in a world where machine translation has become increasingly prevalent, as it ensures that the convenience of automation doesn’t come at the cost of quality.
Why is Machine Translation Post Editing Relevant Today?
In our rapidly globalising world, the need for translation services has never been higher. With international business, education, and cultural exchange all on the rise, the demand for fast and efficient translation is soaring. Enter Machine Translation Post Editing. It combines the speed of machine translation with the finesse of human editing, bridging gaps, and creating connections like never before.
The Evolution of Machine Translation
Early Days
The journey of machine translation began in the 1950s. Early attempts were based on simple word-for-word translation and had limited success. However, they laid the groundwork for future innovations.
“On 7 January 1954 the Georgetown-IBM experiment was held in New York at the head office of IBM. This was the first public demonstration of a machine translation system. The demonstration was widely reported in the newspapers and garnered public interest.”
– The History of Machine Translation, Wikipedia
Transition to Automation
The late 20th century saw the rise of statistical machine translation and neural networks. These approaches allowed for more context-aware translation, opening new possibilities and making automated translation a practical reality.
Latest Developments and Innovations
In recent years, the development of deep learning algorithms and artificial intelligence has further revolutionised the field of machine translation. This has led to the emergence of more sophisticated tools and methods, bringing us closer to translations that are not only accurate but also rich in cultural and contextual nuances.
What is Machine Translation?
Machine Translation (MT) refers to the use of computer algorithms to translate text or speech from one language to another. While it may lack the poetic flair of human translation, MT offers unparalleled speed and scalability.
Machine Translation relies on various methods and models such as rule-based, statistical, and neural machine translation. Each of these approaches has its strengths and limitations, and their selection often depends on specific use cases and requirements.
While Machine Translation has made significant strides in accuracy and fluency, it still falls short when compared to human translation in understanding subtleties, idioms, and cultural expressions. This is where Machine Translation Post Editing comes into play, combining the strengths of both machine and human translation.
What is Machine Translation Post Editing?
Machine Translation Post Editing (MTPE) is the collaboration of artificial intelligence and human expertise. It involves the editing, correction, and refinement of machine-translated texts by skilled human linguists. There are 3 main benefits to consider:
It saves you time
Compared to human translation, MTPE can help you be over twice as productive. Typically, a human translator can roughly translate around 1,500-2,000 words per day. By leveraging machine translation post-editing, this number increases to around 4,000 words per day, depending on the quality of the machine translation engine.
It saves you money
Of course, when you save time – you typically save money. By incorporating MTPE into your translation workflow, you can retain the same level of quality as human translation, due to the editing process.
It’s great for large amounts of text
In business, you may often come across projects where you have to deal with translating large amounts of text in a short period of time. This could consist of training resources, marketing material, reports, or whichever text-based materials are common in your industry. Depending on the type of text and your target audience, MTPE can be an ideal solution.
Machine Translation Post Editing FAQs
What is Machine Translation Post Editing?
Simply put, it is the process of refining and correcting machine-translated texts by human experts.
Why is it MTPE important?
It enhances accuracy, readability, and efficiency in translations.
Who can become a post editor?
Anyone with linguistic skills, cultural understanding, and training in post-editing can pursue a career in this field.
How does it differ from traditional translation?
It combines the speed of machine translation with the finesse of human editing, offering a unique blend of quality and efficiency.
What tools are used in Machine Translation Post Editing?
Various specialised software and platforms are used, depending on the specific requirements and quality standards.
Can I trust machine-translated content without post-editing?
While machine translation has improved, post-editing is often necessary for professional or critical documents to ensure accuracy and quality.
Key Takeaways
Combination of Technology and Human Expertise
MTPE represents the integration of machine translation’s efficiency with human expertise in linguistics and culture. This partnership ensures both speed and quality, allowing for translations that are accurate and resonate with the target audience.
Evolution and Relevance
With the rise of global communication and the advancements in machine learning and artificial intelligence, MTPE has become an essential part of various industries. Its evolution from simple word-for-word translation to sophisticated context-aware algorithms underscores its growing importance and potential.
Variety in Post Editing Approaches
MTPE offers different levels of editing, including Light Post Editing for basic error correction and Full Post Editing for comprehensive refinement. This flexibility allows for tailored solutions to meet specific quality standards and requirements, further enhancing its appeal and applicability.