What is language detection in Azure AI Language?
Language detection is one of the features offered by Azure AI Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. Language detection can detect the language a document is written in, and returns a language code for a wide range of languages, variants, dialects, and some regional/cultural languages.
This documentation contains the following types of articles:
- Quickstarts are getting-started instructions to guide you through making requests to the service.
- How-to guides contain instructions for using the service in more specific or customized ways.
To use this feature, you submit data for analysis and handle the API output in your application. Analysis is performed as-is, with no additional customization to the model used on your data.
Create an Azure AI Language resource, which grants you access to the features offered by Azure AI Language. It will generate a password (called a key) and an endpoint URL that you'll use to authenticate API requests.
Send the request containing your data as raw unstructured text. Your key and endpoint will be used for authentication.
Stream or store the response locally.
Get started with language detection
To use language detection, you submit raw unstructured text for analysis and handle the API output in your application. Analysis is performed as-is, with no additional customization to the model used on your data. There are two ways to use language detection:
|Language studio||Language Studio is a web-based platform that lets you try entity linking with text examples without an Azure account, and your own data when you sign up. For more information, see the Language Studio website or language studio quickstart.|
|REST API or Client library (Azure SDK)||Integrate language detection into your applications using the REST API, or the client library available in a variety of languages. For more information, see the language detection quickstart.|
|Docker container||Use the available Docker container to deploy this feature on-premises. These docker containers enable you to bring the service closer to your data for compliance, security, or other operational reasons.|
An AI system includes not only the technology, but also the people who will use it, the people who will be affected by it, and the environment in which it is deployed. Read the transparency note for language detection to learn about responsible AI use and deployment in your systems. You can also see the following articles for more information:
There are two ways to get started using the entity linking feature: