Document Translation in Language Studio (Preview)

Important

  • Document Translation in Language Studio is currently in Public Preview. Features, approaches and processes may change, prior to General Availability (GA), based on user feedback.

  • Currently, virtual network connectivity isn't supported for the Document Translation feature in the Language Studio.

Document Translation in Azure AI Language Studio is a no-code user interface that lets you interactively translate documents from local or Azure Blob Storage.

Prerequisites

If you or an administrator have previously setup a Translator resource with a system-assigned managed identity, enabled a Storage Blob Data Contributor role assignment, and created an Azure Blob Storage account, you can skip this section and Get started right away.

Note

  • Document Translation is currently supported in the Translator (single-service) resource only, and is not included in the Azure AI services (multi-service) resource.

  • Document Translation is supported in the S1 Standard Service Plan (Pay-as-you-go) or in the D3 Volume Discount Plan. See Azure AI services pricing—Translator.

Document Translation in Language Studio requires the following resources:

Now that you completed the prerequisites, let's start translating documents!

Get started

At least one source document is required. You can download our document translation sample document. The source language is English.

  1. Navigate to Language Studio.

  2. If you're using the Language Studio for the first time, a Select an Azure resource pop-up screen appears. Make the following selections:

    • Azure directory.
    • Azure subscription.
    • Resource type. Choose Translator.
    • Resource name. The resource you select must have managed identity enabled.

    Screenshot of the language studio choose your Azure resource dialog window.

    Tip

    You can update your selected directory and resource by selecting the Translator settings icon located in the left navigation section.

  3. Navigate to Language Studio and select the Document Translation tile:

    Screenshot of the language studio home page.

  4. If you're using the Document Translation feature for the first time, start with the Initial Configuration to select your Azure AI Translator resource and Document storage account:

    Screenshot of the initial configuration page.

  5. In the Job section, choose the language to Translate from (source) or keep the default Auto-detect language and select the language to Translate to (target). You can select a maximum of 10 target languages. Once you select your source and target languages, select Next:

    Screenshot of the language studio basic information page.

File location and destination

Your source and target files can be located in your local environment or your Azure Blob Storage container. Follow the steps to select where to retrieve your source and store your target files:

Choose a source file location

  1. In the files and destination section, choose the files for translation by selecting the Upload local files button.

  2. Next, select âž• Add file(s), choose the files for translation, then select Next:

Screenshot of the select files for translation page.

Choose a target file destination

While still in the files and destination section, select Download translated file(s). Once you make your choice, select Next:

Screenshot of the select destination for target files page.

Optional selections and review

  1. (Optional) You can add additional options for custom translation and/or a glossary file. If you don't require these options, just select Next.

  2. On the Review and finish page, check to make sure that your selections are correct. If not, you can go back. If everything looks good, select the Start translation job button.

    Screenshot of the start translation job page.

  3. The Job history page contains the Translation job id and job status.

    Note

    The list of translation jobs on the job history page includes all the jobs that were submitted through the chosen translator resource. If your colleague used the same translator resource to submit a job, you will see the status of that job on the job history page.

    Screenshot of the job history page.

That's it! You now know how to translate documents using Azure AI Language Studio.

Next steps