The Convert endpoint returns a JSON response containing a message indicating the audio creation status, the URL of the generated MP3 file, and metadata such as the total characters processed and remaining characters available for conversion.

The key fields in the response data include "message" (status of audio creation), "audio_src" (URL of the generated audio file), "error" (indicates success or failure), "total_chars" (number of characters processed), and "remaining_chars" (characters left for conversion).

The Convert endpoint accepts parameters such as "text" (the text to convert), "voice" (to specify gender: male, female, or neutral), and "language" (e.g., "hi_IN" for Hindi). Users can also use "text_premium_" or "ssml_premium_" prefixes for premium voices.

The response data is organized in a JSON format. It includes a top-level object with fields for the message, audio source URL, error status, and character counts, making it easy to parse and utilize in applications.

Typical use cases for the Hindi Text-to-Speech API include creating voice assistants, enhancing accessibility for visually impaired users, generating audio content for e-learning, and providing interactive customer service experiences through voice.

Users can customize their requests by selecting the desired voice gender (male, female, neutral) and specifying the language code. Additionally, they can choose between standard and premium voice options by using the appropriate prefixes in the language code.

The API primarily supports audio output in MP3 format. The input text can be plain text or SSML (Speech Synthesis Markup Language) for more advanced speech features, allowing for greater control over pronunciation and intonation.

Data accuracy is maintained through advanced algorithms and neural networks that analyze and interpret text data. Continuous improvements in machine learning and AI enhance the quality of speech synthesis, ensuring that the output closely resembles natural speech.

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