Detect the language used in text

To detect the language used in a text related to designing and implementing a Microsoft Azure AI solution, you can make use of the Language Detection API provided by Azure Cognitive Services. This API enables you to identify the language of a given text or document. In this article, we will explore how to use this API in your AI solution.

Prerequisites

First, make sure you have created an Azure Cognitive Services resource in your Azure portal. Once the resource is set up, you can obtain the endpoint and access key required for communication with the Language Detection API.

Installation and Setup

To begin, you need to install the Azure SDK for the language of your choice. For example, if you are using Python, you can install the SDK by running the following command:

pip install azure-ai-textanalytics

Next, import the required modules and instantiate the TextAnalyticsClient object with your obtained endpoint and access key:

from azure.core.credentials import AzureKeyCredential
from azure.ai.textanalytics import TextAnalyticsClient

endpoint = “”
key = “”

credentials = AzureKeyCredential(key)
client = TextAnalyticsClient(endpoint=endpoint, credential=credentials)

Detecting Language in Text

Now, you can use the detect_language method provided by the client to detect the language of a given text:

def detect_text_language(client, text):
result = client.detect_language(text)
detected_language = result.primary_language.name
confidence_score = result.primary_language.score

print(f”Detected language: {detected_language}”)
print(f”Confidence score: {confidence_score}”)

text = “This is an example of a text in English.”
detect_text_language(client, text)

The detect_language method takes the input text as a parameter and returns the detected language along with a confidence score. The name property of the primary_language attribute gives you the identified language, while the score property represents the confidence level.

You can also analyze a batch of texts by passing an iterable of strings to the detect_language method:

texts = [“This is an example of a text in English.”,
“Ceci est un exemple de texte en français.”,
“Dies ist ein Beispieltext in Deutsch.”]

for text in texts:
detect_text_language(client, text)
print()

By iterating through each text in the batch, you can obtain the detected language and confidence score for each one.

Conclusion

Azure Cognitive Services provides the Language Detection API, which you can use to identify the language used in a given text related to designing and implementing a Microsoft Azure AI solution. By following the steps outlined in this article, you can easily integrate language detection capabilities into your AI application.