Two distinct methodologies for Machine Translation (MT) stand out for enhancing translation accuracy and relevance: MT Customization and MT Training. While both approaches aim to improve machine-generated translations, they employ different strategies and serve unique needs.
As organizations increase their adoption of Machine Translation (MT) and drive programs to integrate multilingual content, there is a great need to make the output of those MT engines more relevant to the brand, product, or service for which the content will be used. There is also a need to ensure translation accuracy. These are achieved by implementing a complete program involving multiple stages.
MT Customization and MT Training are powerful tools for improving the accuracy and relevance of machine-generated translations. While MT Customization offers a quicker, more accessible way to refine translations through specific linguistic instructions, MT Training provides a deeper, data-driven method for tailoring the MT engine's output to a company's unique requirements.
Let’s delve into the nuances of MT Customization and MT Training.
MT Customization - Tweaking Existing Translations
MT Customization involves modifying an existing Machine Translation engine to better align with specific linguistic preferences and requirements. This is achieved through the integration of a translation glossary and a Do Not Translate (DNT) list. A translation glossary comprises critical terms specific to a company and their corresponding translations, while a DNT list includes terms that the company wishes to exclude from translations, such as product names, branding, logos, etc.
The customization process enhances the MT engine's accuracy by instructing it on how to translate (or not translate) specific terms. This targeted intervention ensures that translations reflect the company's brand identity, adhere to preferred terminologies, and accommodate regional linguistic variations. As a result, the quality of translations improves, reducing the necessity for extensive post-editing.
Implementing MT Customization is generally more straightforward than undertaking MT Training. However, the effectiveness of customization significantly depends on the expertise of the MT specialist managing the process. Skills in selecting the right terms, as well as handling input and output normalization rules, DNT lists, and glossaries, are crucial. A lack of experience can lead to low-quality suggestions from the MT engine, negatively impacting the overall quality of translations. It's also important to note that not all MT platforms support customization, which can influence the choice of MT engine.
MT Training - Teaching the Computer from Scratch
MT Training takes a more foundational approach by creating and refining an MT engine using extensive bilingual data. This data is sourced from corpora and Translation Memories (TMs), which are archives of previously translated content. The training process involves feeding the MT engine with company-specific bilingual data sets, often imported in TM format, which includes not just the translations but also metadata such as the translation date, the linguist's identity, and the degree of match (exact or fuzzy) with the source text.
This rich dataset enables the MT engine to learn and predict the company's translation expectations. Rather than generating generic translations based on a broad interpretation of the source material, the trained engine produces tailored outputs that reflect the specific linguistic and stylistic preferences of the company. Like customization, not all MT platforms are equipped to facilitate training, making platform selection a critical consideration for organizations looking to adopt this approach.
Which Way to Go?
MT Customization and MT Training can both be combined within the same program, as MT Customization can be applied post Training to further refine an engine.
Choosing between MT Customization and MT Training depends on several factors, including the specific use case, the available bilingual data, the MT platform's capabilities, and the expertise of the team responsible for implementing the MT strategy. By carefully considering these aspects, organizations can select the most appropriate method to enhance their translation processes, ensuring high-quality, brand-consistent, and regionally appropriate content.
In the end, it's about making sure the engine's translations sound right and make sense for your company, whether that means giving it a quick lesson or a full-on course.
LanguageLine Can Help
Our experts will work with organizations looking to adopt MT, carefully considering these aspects as well as other factors like automatically estimating the quality of the engines or implementing human quality control mechanisms to enhance their translation processes.
Want to learn more? Contact us at translation@languageline.com to learn about how we can help you create a customized MT program that aligns with your needs.
