To use this API, users must enter a word or text to identify multiple languages.

The Idiom Tracker API allows users to detect and track the language of text-based content in real time.

There are different plans to suit all tastes, including a free trial for a small number of requests, but your rate is limited to avoid abuse of the service.

Zyla provides a wide range of integration methods for almost all programming languages. You can use these codes to integrate with your project as you need.

The Language Detection endpoint returns a JSON array containing detected languages along with their confidence scores. Each entry indicates the language identified and the likelihood that the detection is accurate.

The key fields in the response data are "language," which specifies the detected language, and "confidence," which indicates the certainty of the detection on a scale from 0 to 1.

The response data is organized as a JSON array, where each object contains the detected language and its corresponding confidence score. This allows users to easily parse and utilize the information.

The primary parameter for the Language Detection endpoint is the input text, which can be a single word or a longer string. Users can customize their requests by providing different text inputs for detection.

Data accuracy is maintained through advanced natural language processing algorithms and machine learning methodologies that continuously improve language detection capabilities based on diverse datasets.

Typical use cases include multilingual customer support routing, content localization for different markets, and social media monitoring for sentiment analysis across various languages.

Users can utilize the returned data by analyzing the confidence scores to determine the most likely language and making decisions based on the highest confidence level, enhancing user experience in multilingual applications.

Standard data patterns include multiple languages detected in a single input, with varying confidence scores. Users may encounter cases where one language has a significantly higher confidence than others, indicating a primary language presence.

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