Natural Language Processing in Microsoft Azure-Translation service

Khalida Douibi
2 min readMay 28, 2024

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Summary from my learning journey in Coursera inspired from Coach (GenAI tool)

Robot translating text generated by Designer from copilot May 28, 2024

The Translator Text service supports translation between more than 60 languages and allows you to specify cultural variants of languages. The service also offers optional configurations for profanity filtering and selective translation. The Speech service includes APIs for speech-to-text, text-to-speech, and speech translation, which can be used for real-time closed captioning and simultaneous two-way translation of spoken conversation. The page provides information on specifying source and target languages and the format to use.

Let’s deep dive into the key components of the Translator Text service in Microsoft Azure are as follows:

  1. Neural Machine Translation (NMT) Model: The Translator Text service uses a neural machine translation model for translation. This model analyzes the semantic context of the text, resulting in more accurate and complete translations.
  2. Language Support: The Translator Text service supports text-to-text translation between more than 60 languages. You can specify the language you’re translating from and the language you are translating to using ISO 639–1 language codes. Additionally, you can specify cultural variants of languages by extending the language code with the appropriate 3166–1 Cultural Code.
  3. Text Translation: The Translator Text service allows you to integrate text translation into your applications, websites, tools, and solutions. You can specify one source language and multiple target languages, enabling you to simultaneously translate a source document into multiple languages.
  4. Optional Configuration: The Translator Text API offers optional configurations to fine-tune the translation results. Two examples of these configurations are profanity filtering and selective translation.
  • Profanity Filtering: By using profanity filtering, you can control how profanity is handled in the translated text. You can choose to mark the translated text as profane or omit it in the results.
  • Selective Translation: Selective translation allows you to tag content that should not be translated. For example, you can tag code, brand names, or words/phrases that don’t make sense when localized.

These components work together to provide a powerful and flexible translation solution in Microsoft Azure.

For live demo about those services check my Youtube channel AI4Innovation

#microsoft #azure #NLP #naturalLanguageProcessing #

References

https://learn.microsoft.com/en-us/training/modules/translate-text-with-translation-service/

https://www.coursera.org/learn/nlp-microsoft-azure

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Khalida Douibi

Sn. Data Scientist. PhD. Biomedical Informatics, Machine learning