Custom Translator, now in general availability, significantly improves the quality of your translations by letting you build your own customized neural translation models tuned with your own pre-translated content. Using Custom Translator, you can translate your product names and industry jargon just the way you want.
With Custom Translator, an extension of the Microsoft Translator Text API, part of the Cognitive Services suite of products on Azure, you can build neural translation models that understand the terminology used in your own business and industry. The customized translation model will then seamlessly integrate into existing applications, workflows, and websites.
Custom Translator can be used with Microsoft Translator’s advanced neural machine translation when translating text using the Microsoft Translator Text API and speech translation using the Azure Cognitive Services Speech Service.
Preview customers of Custom Translator have already noted its improvements on translation quality and its usefulness regardless of the amount of pre-translated, bilingual content available.
Alex Yanishevsky, Senior Manager for machine translation at Welocalize, a leading language service provider, remarked, “Using , we’ve seen very good quality in comparison to other engines. It is very flexible. You can make engines just based on dictionaries if you don’t have enough data, and if you do have enough data you can make an engine based on data plus dictionaries. From the standpoint of customization, having that flexibility is really important.”
Custom Translator is easy to use and does not require a developer once the call to the Translator service has been properly set up in your app’s code. Custom Translator features a simple and intuitive web app that guides you through the 4-step process of customizing a model:
View the process in the image below.
For advanced use, there is also the Custom Translator API (preview) to automate the customization into your workflows.
Building and using custom NMT with Translator is quick, easy, and cost effective. By optimizing how training is performed, and how the Translator runtime incorporates the custom training, our team was able to provide a solution for customizing the Translator NMT models with a training cost that is less than 1% of the cost of training a new neural translation model from scratch. This, in turn, enables Microsoft to provide a cost-effective and simple pricing model to our users.
General availability pricing will go into effect on February 1st, 2019.