Project Description:

The Real-Time Language Translator (AI) is a web-based application that allows users to input text or speech in one language and instantly translates it into another, using machine learning-based Natural Language Processing (NLP) models. This project can support live chat, subtitles, or conversation translation in real-time, making it ideal for travel, education, customer support, or multicultural team collaboration.

Key Features:

Multilingual Text & Voice Translation:

• Input can be text typed by the user or speech via microphone.

• The output appears in the selected target language as text and optionally as speech (text-to-speech).

• Uses NLP models (e.g., Transformer-based models like BERT, MarianMT, or OpenNMT) for translation.

• Option to translate between major languages like English, Hindi, French, German, Chinese, etc.

Frontend:

• Developed using HTML, CSS, Bootstrap, JavaScript.

• Includes:

  • Input box and microphone toggle for speech input.

  • Language selection dropdowns (From & To).

  • Live translation area.

  • Audio playback for translated speech.

  • Chat-style interface (for conversation mode).

Backend:

• Developed using PHP, Java, or Node.js.

• Performs:

  • API integration with translation services like Google Translate API, Hugging Face models, or custom ML models.

  • Text preprocessing and cleaning.

  • Storing translation logs (for learning history or analytics).

  • Authentication and user profiles (for saving preferences).

AI/ML Integration:

• Use pre-trained models such as:

  • MarianMT (Hugging Face) – multilingual transformer model.

  • Google's Translation API (for plug-and-play solutions).

• For advanced users: Train a custom sequence-to-sequence model using datasets like Tatoeba, EU Bookshop corpus, etc.

• Implement Text-to-Speech (TTS) using APIs like gTTS, Amazon Polly, or Microsoft Azure TTS.