AWS Machine Learning Blog
Translating presentation files with Amazon Translate
As solutions architects working in Brazil, we often translate technical content from English to other languages. Doing so manually takes a lot of time, especially when dealing with presentations—in contrast to plain text documents, their content is spread across various areas in multiple slides. To solve that, we wrote a script that translates Microsoft PowerPoint files using Amazon Translate. This post discusses how the translation script works.
Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. When working with Amazon Translate, you provide text in the source language and receive text translated into the target language. For more information about the languages Amazon Translate supports, see Supported Languages and Language Codes.
The translation script is written in Python and relies on an open-source library to parse the presentation files.
Solution
The script requires three arguments:
- Source language
- Target language
- File path of a .pptx file
The script then performs the following functions:
- Parses the file
- Extracts its texts
- Invokes the Amazon Translate API for each text
- Saves a new file with the translated texts that the API returns
The following command translates a presentation from English to Portuguese:
To interact with Amazon Translate, the script uses Boto, the AWS SDK for Python. Boto is configurable in multiple ways. Regardless, you must have AWS credentials and a Region set to make requests to AWS. Here is more information about Configuration Credentials.
To handle presentation files, the script uses python-pptx
, an open-source library available on GitHub. When you provide a presentation file path as input, the library returns a Presentation
object. See the following code:
Within a Presentation
object, there are slides and, within the slides, shapes and their paragraphs. You can iterate over all paragraphs and invoke the Amazon Translate API for each text. Amazon Translate offers two different translation processing modes: real-time translation and asynchronous batch processing. The script uses the former, which allows you to call Amazon Translate on a piece of text and synchronously get a response with the corresponding translation. See the following code:
You then get the translated text from the API to replace the original text. See the following code:
The script replaces not only the visible presentation text, but also its comments. Moreover, the script has a map to update the language identifiers. That’s necessary to indicate the correct language so Microsoft PowerPoint can properly check the spelling. See the following code:
In addition to passing a text, the source language, and the target language, you can use the Custom Terminology feature of Amazon Translate which makes sure that it translates terms exactly the way you want. To do this, you need to pass a list of pre-translated custom terminology when invoking the API. For instance, you can customize the translation of technical terms, put those terms and their respective translations in a CSV file, and pass its path as an optional argument to the script. The script reads the file and imports its content into Amazon Translate. See the following code:
After translating all the slides, you save the presentation as a new file with the following code:
The script is straightforward, but very useful. For the full code, see the GitHub repo.
Conclusion
This post described a script-based solution to translate presentation files using Amazon Translate into a variety of languages. For more information, see What Is Amazon Translate?
About the Authors
Lidio Ramalho is Senior Manager on the AWS R&D and Innovation Solutions Architecture team. He works with customers to build innovative prototypes in AI/ML, Robotics, AR VR, IoT, Satellite, and Blockchain disciplines.
Rafael Werneck is a Solutions Architect at AWS R&D, based in Brazil. Previously, he worked as a Software Development Engineer on Amazon.com.br and Amazon RDS Performance Insights.