🌐 Anuwad: Transforming Regional AI Translation 🤖

📝 Problem Statement

Language barriers limit communication across languages, affecting collaboration and access to information. Anuwad aims to solve this by:

• Converting speech to text 🎤
• Translating it into different languages 🌍
• Converting the translated text back into speech 🔊

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🔑 Key Features

1. Real-Time Speech Recognition 🎧

• Converts speech to text using Speech-to-Text (STT) 📝.
• Supports various Indian languages (Hindi, Kannada, Marathi, etc.).
• Handles diverse accents and dialects.

2. Language Translation 🌏

• Translates text from mentor’s language to user’s native language 🔄.
• Uses IndicTrans2 models for accurate translations.
• Fallback for unsupported languages 🛠️.

3. Text-to-Speech (TTS) 🗠️

• Converts translated text back to speech using Google TTS 🔊.
• Multiple voice options for a natural-sounding output 🎶.

4. Bidirectional Communication 🔄

• Allows communication in both languages (mentor & user).
• Toggle feature for seamless switching 🔄.

5. Language Selection 🌍

• Users select their preferred language from a list 🌐.
• Automatic language detection for ease ⚡.

6. User Interface (UI) 🖥️

• Simple, intuitive interface for users 👨‍💻.
• Visual cues for real-time translation and speech status 👁.
• Optimized for accessibility (large fonts, screen reader compatible) 💡.

7. Scalability & Performance 🚀

• Optimized for multiple users simultaneously 🌟.
• Low-latency for real-time communication ⏱️.

8. Security & Privacy 🔒

• No sensitive data storage ❌.
• Encrypted data transmission 🔐.

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⚙️ Tech Stack

• Frontend: React.js ⚛️
• Backend: Flask 🐍
• Authentication: Firebase Authentication 🔑
• Speech Recognition: Webkit Speech Recognition 🎤
• Text-to-Speech (TTS): Google TTS 🔊
• Translation: IndicTrans2 Models 🌍

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🖼 Screenshot

Here’s a glimpse of the application interface:

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🚀 Future Enhancements

• Offline functionality for STT & TTS 🛲.
• Option to save/export translated conversations 💾.
• Integration with messaging/video platforms 📱📩.
• Teacher-Student Platform Integration: 👨‍🏫
  • Teachers will be able to upload their audio lessons via a login portal.
  • Students can access lessons in their preferred language.
  • A centralized dashboard for teachers to manage uploaded content and track engagement.

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📺 Deployed link of Anuwad

Click here! 🎬

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Status

Implemented:

1. Real-Time Speech Recognition:

   • Speech-to-Text (STT) implemented.
   • Supports multiple Indian languages (Hindi, Kannada, Marathi, etc.).

2. Language Translation:

   • Text is translated from mentor’s language to the user’s native language.
   • Translation is handled using IndicTrans2 models.

3. Text-to-Speech (TTS):

   • Converts translated text to speech using Google TTS.

4. Bidirectional Communication:

   • Users can communicate in both languages (mentor & user).
   • Toggle feature to switch between languages seamlessly.

5. Language Selection:

   • Language selection dropdown for users to choose their preferred language.

6. User Interface (UI):

   • Simple, intuitive interface with visual cues for real-time translation and speech status.
   • Optimized for accessibility (large fonts, screen reader compatible).

7. Backend & Frontend:

   • Backend implemented using Flask.
   • Frontend developed using React.js.

8. Authentication Pages:

   • Firebase project created & Authentication pages completed.

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Remaining Tasks:

1. Security & Privacy:

   • Implement data encryption for secure transmission.
   • Ensure no sensitive data storage (currently pending).

2. Teacher-Student Module Integration:

   • Develop a teacher login portal.
   • Enable video uploads for lessons.
   • Build a student interface to access lessons in their native language.

3. Deployment on Cloud:

   • Deploy web application on Vercel Cloud Platform**.

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📧 Contact

For further inquiries, reach out to me at: Shubham Murtadak ~ AI Engineer 📩.

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