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ASL Dictionary Home Page

ASL Dictionary Web App

The ASL Dictionary Web App is a comprehensive platform that allows users to explore, practice, and contribute to the world of American Sign Language. With a variety of features, this app aims to be a valuable resource for both ASL learners and experts.

Features

  1. View Topics: Users can browse through different topics or categories of signs, making it easier to find the signs they're interested in.

  2. View Words: Users can view detailed information about individual ASL signs, including the sign's meaning, handshape, location, and movement.

  3. Practice with Flashcards: Users can use the built-in flashcard feature to practice signing the words they've learned, helping to reinforce their knowledge.

  4. Create Own Words: Registered users can contribute to the dictionary by creating and submitting their own ASL signs, ensuring the app is continuously expanding its content.

  5. Like Words: Users can express their appreciation for signs by liking them, which helps the app's algorithms to surface the most popular and useful signs.

  6. Rate Words: Users can rate the quality and accuracy of the signs in the dictionary, providing feedback that can be used to improve the app's content.

  7. Request Words: Users can request the addition of new signs to the dictionary, which the app's administrators can then review and potentially add.

  8. Statistics: The app provides users with statistics and insights about the most popular signs, trending topics, and user engagement metrics.

  9. Manage Users: App administrators can manage user accounts, including approving new user registrations and monitoring user activity.

  10. Sign Recognition: The app includes a feature that allows users to use their device's camera to capture and recognize ASL signs, providing real-time feedback and suggestions.

Technology Stack

The ASL Dictionary Web App is built using the following technologies:

  • Front-end: React.js, HTML, CSS, JavaScript
  • Back-end: Node.js, Express.js
  • Database: MongoDB
  • AI/ML: TensorFlow.js for sign recognition

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