Machine translation (MT) offers promising benefits for organizations to speed up time to market, translate larger volumes, and maintain content consistency. It’s impossible to ignore the potential rewards of going to market faster and more cost effectively.
Be that as it may, implementation of these technologies is a strategic move that requires careful thought and planning to achieve the results your business might want. We’ve compiled a list of key questions to consider when formulating your approach to help increase your odds of success.
1. What are your business objectives?
To successfully implement MT, find your why. What are you trying to achieve? Depending on your organization’s size, type, and industry, these objectives could include goals including:
- Maximizing the impact of your localization budget
- Shaving precious days or even weeks off your time-to-market
- Providing better support for diverse consumers
- Improving workflows and communication within your organization
- Increasing customer satisfaction with a more consistent in-language experience
Use these to guide the decisions you make during the implementation process. They'll influence the technology you choose, the workflows you adapt, and even the way you evaluate success.
2. Which languages need translation?
Not all language pairs are created equal with MT. Some languages, such as French or Spanish, can achieve higher-quality results thanks to large datasets. Less common languages will present more quality challenges due to a lack of training data.
Weigh linguistic complexity against the market demand for each language. Will a less commonly spoken or complex language offer enough ROI to justify the potential challenges in translating it and post-editing the copy?
Your target languages may also influence which MT tool is the best fit for your organization, as some engines perform better in different languages than others.
3. What type of content and volume will be translated?
MT excels at handling large volumes of user-generated content, where speed and scalability matter more than pinpoint accuracy. It also excels at translating product descriptions and technical documents, where the language tends to be more standardized.
The more creative the content is, the less suitable it is for MT. Translation of nuanced, emotional, and/or highly branded content is about more than words. High-visibility content that’s made to engage or entertain your audience typically requires a human touch.
4. Do you have high-quality training data and an up-to-date glossary?
For AI-powered MT approaches like neural machine translation (NMT), the tool is only as good as the data it’s trained on. You can make sure that MT will produce results that align with your business goals by feeding it high-quality training data.
Most MT engines start with a generic data set but adding custom data from your Translation Memory (TM) helps fine-tune for better results. Make sure to audit and update your TM to ensure it is free from inconsistencies, duplicate entries, and irrelevant or outdated content.
A glossary will also tell translators (machine or human) how you’d like different terms, words, or phrases to be translated. An up-to-date glossary ensures consistency across all of your content and preserves your brand voice across different languages.
5. Which MT model fits your needs?
Approaches to MT have evolved significantly in the past decade, each model excels in different areas. Choosing the right one is all about zeroing in on your business goals for MT, ULG's machine translation services can be an invaluable resource to help you understand your options and select the right tools for the job.
- Neural Machine Translation (NMT) utilizes deep learning models and neural networks to predict sequences of words, producing highly natural and fluent translations. NMT is widely adopted due to its ability to handle complex language structures and generate high-quality translations with context awareness.
- Large Language Models (LLMs) are trained on a diverse range of internet text and can perform translations by predicting the next word in a sequence. LLMs are popular for their flexibility and ability to handle creative and nuanced translation tasks, although they might still lag behind NMT in specific language pair accuracy.
- Custom models use a pre-trained NMT model that is fine-tuned on a smaller dataset or built from scratch to meet specialized requirements, such company specific terminologies. They provide a tailored approach to translation, ensuing high accuracy and consistency in particular domains or use cases.
6. Do you have a strategy for post-editing translated output?
Automated translations are rarely perfect right out of the box (this is referred to as “raw MT”). Human review and editing are necessary to elevate machine-generated translations to the level of quality your brand and audience expect.
Certain sectors require more post-editing than others: in sectors such as healthcare a mistranslation could change the course of someone’s life, and so post editing by skilled linguists with relevant expertise and training is a must.
It's important to plan how the machine-translated content will be reviewed and edited. Will you rely on in-house experts? Or outsource to professional language service providers? An effective MTPE process requires experience, training, and expertise in the relevant subject matter.
7. What are your data privacy and security requirements?
The trade-off to free or publicly available MT technologies is the lack of data privacy and security. If your business deals with sensitive consumer data or the content to be translated includes your organization’s intellectual property, it is not worth the risk.
Ensuring these requirements are met when implementing MT involves a combination of best practices and selecting the right tools and providers. A trusted partner like ULG can guide you through our secure solutions that include robust measures to keep your data safe.
8. Can you integrate MT into your existing workflows and systems?
Incorporating MT into your current workflows requires a deep understanding of your existing processes and a clear vision of when and where your new technology should intersect and integrate. It may even involve updating or even overhauling your current systems.
These changes could range from introducing new software connectors that enable smooth data flow between your MT system and content management systems (CMS) to modifying content creation practices in your translation workflows to better suit MT requirements.
Remember, MT isn't just a tool; it's a part of your larger content strategy and needs to be seamlessly integrated into your existing ecosystem for maximum efficiency.
9. What quality and performance metrics will you use?
MT quality evaluation is the process of assessing the quality of machine translation output by comparing it to human translations. Metrics like BLEU, NIST, and TER score how closely MT text aligns with reference translations, ensuring the translation meets certain standards of accuracy.
And how will you know if MT is working for your business? Establish key performance indicators (KPIs) that align with your original motivations for adopting MT. This strategic direction will help you understand how your processes are performing, along with where it needs to be adjusted.
10. Have you run an AI translation pilot and considered your budget?
A pilot test can help you make data-driven decisions before you commit to full-scale implementation. It will provide you with insight into how well the MT system integrates with your existing workflow, the quality you can expect, and any unforeseen challenges.
To truly understand the impact of MT on your processes, you need a hands-on opportunity to experience the benefits directly – tailored to your specific requirements. ULG can show you real results to help make strategic choices with our AI Translation Pilot.
When budgeting for MT, consider not just the upfront costs but also the ongoing expenses for maintenance and improvements. Remember to factor in the benefits that an effective MT strategy can yield – from increased translated content volume to quicker time-to-market.
Preparing for AI-Powered Machine Translation
Machine translation solutions can be a gamechanger for organizations, it helps reach more markets, at a quicker pace, and can optimize your budget spend. It’s not always simple to implement, but ULG can help you design a strategy that will guide you to success.
Contact us for a consultation today!
