Multilingual Detector API

The Multilingual Detector API is a tool that allows users to determine the language of a given piece of text with a confidence score.

About the API:

The Multilingual Detector API is a powerful tool for developers and businesses that require accurate and efficient language detection capabilities. It is designed to analyze a few sentences of text and determine the language of the text with a confidence score, which makes it a valuable asset for applications that require multilingual support.

The Language Detector API uses advanced algorithms and machine learning models to analyze the input text and determine the language.

One of the key features of the Language Detector API is its speed and accuracy.

The Multilingual Detector API can be easily integrated into existing applications through its user-friendly API. Developers can quickly and easily access the API and receive the results in a JSON format that can be easily parsed and integrated into their applications.

Overall, the Language Detector API is an essential tool for businesses and developers that require multilingual support. Its accuracy, speed, and ease of use make it a valuable asset for any application that needs to analyze text in multiple languages.

What your API receives and what your API provides (input/output)?

It will receive a parameter and provide you with a JSON.

What are the most common uses cases of this API?

  • Content filtering: Websites or social media platforms can use the Multilingual Detector API to filter out posts or comments that are not in the desired language.
  • Customer support: Businesses can use the Multilingual Detector API to automatically detect the language of customer inquiries and route them to agents who speak that language.
  • Translation services: Language detection is an important first step in any translation service, and the Multilingual Detector API can help automate that process.
  • Multilingual chatbots: Chatbots can use the Multilingual Detector API to determine the language of user inputs and respond in the appropriate language.
  • Language learning: Language learning apps can use the Multilingual Detector API to automatically detect the language of input texts and provide translations or explanations to help learners understand the text.
  • Multilingual search: Search engines can use the Multilingual Detector API to provide more relevant search results by automatically detecting the language of the user's query.
  • Voice assistants: Voice assistants like Siri or Alexa can use the Multilingual Detector API to understand the language of user inputs and respond accordingly.
  • Sentiment analysis: Sentiment analysis tools can use the Multilingual Detector API to classify the language of customer reviews or social media posts and analyze sentiment in different languages.
  • E-commerce: Online retailers can use the Multilingual Detector API to automatically detect the language of customer reviews and display them in the appropriate language.

Are there any limitations to your plans?

Besides the number of API calls, there are no other limitations.

API Documentation

Endpoints


The Detector endpoint is a key feature of the Multilingual Detector API, which allows users to determine the language of a given piece of text with a confidence score. By submitting a few sentences to the Detector endpoint, the API can analyze the input and accurately determine the language of the text. The confidence score provided by the endpoint gives users a measure of how confident the API is in its language detection. This endpoint is essential for any application that requires language detection capabilities, such as multilingual chatbots, translation services, or sentiment analysis tools.



                                                                            
GET https://zylalabs.com/api/1999/multilingual+detector+api/1766/detector
                                                                            
                                                                        

Detector - Endpoint Features

Object Description
text [Required]
detectedcount [Optional]
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"status":"ok","timestamp":1683650701163,"data":[["english",0.3280200501253133],["french",0.21230576441102755]]}
                                                                                                                                                                                                                    
                                                                                                    

Detector - CODE SNIPPETS


curl --location --request GET 'https://zylalabs.com/api/1999/multilingual+detector+api/1766/detector?text=The Detector endpoint is a key feature of the Multilingual Detector API, which allows users to determine the language of a given piece of text with a confidence score.' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Multilingual Detector API REST API, simply include your bearer token in the Authorization header.
Headers
Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Multilingual Detector API FAQs

The Detector endpoint returns a JSON object containing the detected languages and their corresponding confidence scores. This allows users to understand not only the identified languages but also the level of certainty associated with each detection.

The key fields in the response data include "status," "timestamp," and "data." The "data" field contains an array of detected languages paired with their confidence scores, indicating the likelihood that the text is in that language.

The returned data is in JSON format. It includes a "status" field indicating the request's success, a "timestamp" for when the request was processed, and a "data" array with language-confidence pairs, e.g., [["english", 0.32], ["french", 0.21]].

The Detector endpoint accepts a single parameter: the text input for language detection. Users can submit a few sentences, and the API will analyze this text to determine the language.

The response data is organized into three main components: a status message, a timestamp, and a data array. The data array contains sub-arrays for each detected language and its confidence score, allowing for easy parsing and analysis.

Typical use cases include content filtering, customer support routing, translation services, multilingual chatbots, and sentiment analysis. The API helps automate language detection, enhancing user experience in multilingual environments.

Data accuracy is maintained through advanced algorithms and machine learning models that continuously learn from diverse text samples. Regular updates and quality checks ensure the API remains reliable in detecting various languages.

If the API returns partial or empty results, users should check the input text for clarity and completeness. Implementing error handling in the application can help manage such scenarios, ensuring a fallback mechanism is in place for user experience.

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