Machine translation based on large language models (LLMs) has come to CAT tools and TMS. We’re announcing the TMS integration with Google Adaptive Translation, which leverages Google’s LLMs to produce more fluent and natural-sounding translations. Through Custom.MT Console, Google Adaptive Translation is now available in Trados, memoQ, and Smartling.
Google Adaptive Translation is a new product in beta, developed in 2023 and launched in public preview on December 12. It is one of the first switches of machine translation from smaller neural networks to larger models, and a precursor to the time when most automated translation will be LLM-based.
The product goes into General Availability before the end of February 2024.
Improved Fluency
Our team participated in the early test of Adaptive Translation in the summer of 2023. Comparing Adaptive and customized models built on Google Translate AutoML with three enterprise clients, we saw that linguists always favored Adaptive Translation, even when BLEU/COMET scores did not. Adaptive produces more varied, nuanced, and fluent language than AutoML, it diverts from literal translations but stays true in the effect on the audience.
Free customization
Another key advantage of Adaptive Translation over AutoML is that it is considerably easier to customize. Adapting the model does not require a large dataset, nor does it take a computational budget. A machine translation engineer can quickly iterate on the model output and fix errors without a budget.
Limitations
Because Adaptive Translation is a new product, there are several limitations. It supports a limited number of languages: English in combination with French, Italian, German, Spanish, Chinese, Korean, Japanese, and Arabic, Russian, Portuguese & Thai on request. The number of characters per request is 512 max, which supports most segments but may not work with extremely long software strings or document context. The glossary function has not been implemented yet, it’s only possible to customize with translation memories, not term bases. Finally, Adaptive is much slower than AutoML, and may take 1-4 seconds to translate a segment.
Here is a table summarizing the differences between AutoML v3, the current go-to product to customize Google Translate, and the beta version of Adaptive Translation.
Competition
Google Adaptive Translation is coming to the market where several products bear the same name and offer easy customization. The following MT brands offer adaptive: ModernMT, Amazon ACT, Lilt, Language Weaver, and a few others. Approaches to making machine translation adaptive differ, but the central benefit is to get a quick feedback loop for human feedback to alter the machine algorithm. It’s the ability to learn on the fly from user corrections.
Google’s key differentiators are that the product is based on a large language model and that its cost is lower. Google Adaptive comes with a price tag of $25 per million characters, compared to ModernMT’s $100 per million for LSPs, and Amazon ACT’s $60 per million.
A Wider GenAI Adoption in the Industry
Generative AI is quickly being adopted for translation in various ways, from bare-bones OpenAI integrations to a mix of traditional MT + automated post-editing with prompts. Examples include:
- aggregators that plug OpenAI into user applications (Custom.MT, Intento, Blackbird, Zapier)
- LLM-boosted machine translation: Globalese engines are enhanced by OpenAI + custom prompts, similar developments are ongoing at BWX, Omniscien, and other organizations.
- Roblox trained their own generative AI model for translation
- California government is seeking an implementation of GenAI for translation
In 2024, machine translation providers will likely all adopt generative AI as a new way of producing translations, either as a parallel product to existing neural MT, or as a combination of the classic and the new. Google Translate launched its offering ahead of others.
Example: Globalese interface to activate OpenAI boosting for MT engines built on MarianNMT
Setup in Custom.MT Console
Adding Google Adaptive Translation at the moment requires engineering skills with Google Control Panel, and to streamline the experience, Custom.MT provides the configuration as a service. Here are the steps to complete it on your own:
Add a dataset in the Google Control Panel. Adaptive Translation requires you to provide several examples of translation, the bare minimum is 5 and the maximum is 30,000 sentence pairs if you’re using the API. Because most translation memories are larger, we recommend doing a terminology detection run in a CAT tool, and adding sentences with terminology to your Google dataset.
Configure a custom model in Custom.MT Console. In your console.custom.mt account, navigate to Translation > Credentials. Scroll to the bottom of the page to see Custom Engines and click Create New. This will open a dialog box where you can add the Google Adaptive keys, including project_id and dataset_id. A successfully configured model will show in green as Available on the Credentials page.
Add a template. Navigate to Translation > Templates and create a new template. Select the language, and you will your model name in the dropdown list of models. You will then be able to save the template and select it when translating from Trados, memoQ, and Smartling. Please note that Google Adaptive doesn’t support local language varieties, i.e. French, but not French (Canada).
Business Information
To start with Google Adaptive Translation via Custom.MT, we offer two options:
Self-service: configure Google Adaptive in Google Control Panel, then connect to Custom.MT console on your own. Note that you may only add 10k segments as examples through the user interface.
Full-service: our engineer will prepare your translation memory, customize Adaptive Translation, run metrics, and connect your TMS at €900 per language combination.
To request a full-service implementation, please contact info@custom.mt
Documentation
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