AI SIGNBRIDGE

AI SignBridge – Communication Without Barriers

Inspiration

Communication is a basic need in everyone's life. We use communication everywhere, whether it is talking to our family, asking for help, visiting a hospital, going to a bank or attending college. But for people who mainly use sign language, communicating with someone who does not understand sign language can sometimes be difficult.

We started thinking about this problem and how technology could help. We felt that this problem can become more serious in places like hospitals, emergency services, banks, government offices and educational institutions, where communication needs to be quick and clear.

At first, we thought about creating a simple sign language translator. But while discussing the idea, we felt that just converting signs into text would not be enough. We wanted to create something that could support communication in both directions.

This is how we came up with AI SignBridge – Communication Without Barriers.

Our idea is to use AI, computer vision, speech processing, NLP and a 3D avatar to create a bridge between people who use sign language and people who communicate through speech or text.

The Problem

People who use sign language may face communication difficulties when the person in front of them does not know sign language. In normal situations this can already be challenging, but in places like hospitals or emergency situations, even a small communication problem can make things more difficult.

Some existing solutions may have limited sign vocabulary or may support only one-way communication. They may also not provide enough support for different real-life situations.

For example, a person in a hospital may need to quickly communicate about pain, medicine or an emergency. A general translator may not always provide the right words or options quickly.

We wanted to solve this by creating a system that can support communication in both directions and also provide different options based on the situation.

What AI SignBridge Does

AI SignBridge is an AI-based communication platform that connects:

Sign Language ↔ Text ↔ Speech

The main idea is to allow two people to communicate even when they use different communication methods.

A sign-language user can show a supported sign in front of the camera. The system detects the hand, identifies the sign and converts it into text. The text can also be converted into speech.

In the other direction, a person can speak to the system. The speech is converted into text, processed by the system and mapped to a supported sign sequence. The sign is then displayed through the 3D avatar.

Users can also type a message directly, and the system can select the available sign animations for the avatar.

AI-Based Sign Recognition

One of the main parts of our project is sign recognition.

The user shows a supported sign in front of the camera. The system first detects the hand and collects the hand landmarks. These landmarks are then processed to recognize the supported sign.

The basic flow is:

Camera Input → Hand Detection → Landmark Extraction → Feature Processing → Sign Recognition → Confidence Score → Text

This allows the system to convert a user's supported sign into understandable text.

3D Sign-Language Avatar

Another important part of AI SignBridge is our 3D avatar.

Instead of showing only the translated text, we wanted the response to be shown visually as well. The avatar can perform supported sign animations and combine multiple signs into a sequence.

We also wanted the user to have control over the animation. So the avatar can support features such as play, pause, replay and animation speed control.

This gives users a more visual way to understand the communication.

Context-Aware Communication

While working on the idea, we realized that communication is different depending on the situation.

For example, the words needed in a hospital are different from the words needed in a bank.

So we planned different modes in AI SignBridge:

Hospital Mode

Emergency Mode

Bank Mode

Government Mode

Education Mode

General Communication

For example, Hospital Mode can provide commonly needed words such as Doctor, Pain, Medicine, Allergy, Appointment and Emergency.

This makes the system more focused instead of giving the user a large list of unrelated words.

Emergency Mode

Emergency situations require communication to be quick and simple.

So we included an Emergency Mode with commonly needed phrases such as:

I need help

Call an ambulance

I am injured

I need a doctor

I am in danger

I cannot hear

I cannot speak

Please call my emergency contact

The idea is to make these important options easy to find without going through many screens.

AI SignBridge is designed as a communication support system and is not meant to replace emergency services or professional interpreters.

Two-Person Conversation Mode

We also wanted AI SignBridge to support an actual conversation between two people.

One person can use sign language while the other person can use speech or text.

For example:

Sign Language → AI → Text/Speech

and

Speech/Text → AI → Sign-Language Avatar

The conversation can be shown with the messages and their input methods, making it easier for both people to follow what is being communicated.

Practice Mode

We also thought that the system could be useful for people who are learning supported signs.

In Practice Mode, the 3D avatar can demonstrate a supported sign. The user can then try to perform the same sign in front of the camera.

The system can recognize the attempt and provide the recognition result and confidence information.

This makes the project not only a communication tool but also a simple way to practice supported signs.

Multilingual Support

We want AI SignBridge to be useful for more people, so our interface is designed to support:

English

Tamil

Hindi

The same idea can be extended to more Indian languages in the future.

Accessibility

Accessibility is one of the important parts of our project.

We want the interface to be easy for different users to understand and operate.

Some of the features include:

High-contrast mode

Adjustable font size

Caption-size controls

Keyboard navigation

Reduced-motion support

Large emergency controls

Clear visual feedback

Voice output

Responsive design

Our aim is to make the system simple instead of making it complicated for the user.

Privacy

Since our project can use the camera, microphone and communication information, we also considered privacy while designing it.

The system can ask for permission before using the camera or microphone. We also want to avoid unnecessary recording and storage of conversations.

We considered features such as secure authentication, API key protection, input validation and role-based access.

Our goal is to use only the information needed for the communication process.

Innovation

The main idea behind AI SignBridge is that we are not focusing only on sign recognition.

We are bringing different technologies together to create a communication system.

It combines:

Computer Vision + AI/NLP + Speech Processing + Context Awareness + 3D Animation + Accessibility

We are also not claiming that the current system can translate every sign language sign. Our prototype works with a defined supported vocabulary.

This makes the current project more realistic, while giving us the possibility to add more signs, languages and datasets in the future.

How We Built It

We divided the project into different parts so that each part has a specific role.

For the frontend, we use technologies such as React / Next.js, Tailwind CSS and Framer Motion to create the interface.

For computer vision, we use MediaPipe and TensorFlow.js / ONNX Runtime for hand landmark detection and sign recognition.

For AI and NLP, the system handles things such as text processing, intent detection, context detection, supported phrase matching and sign-sequence selection.

For the 3D avatar, we use Three.js and React Three Fiber along with reusable sign animations.

For the backend, we use Python FastAPI / Node.js for APIs and the AI service layer.

For storing required information, the architecture can use PostgreSQL / MongoDB.

We also considered authentication, API validation, environment variables and privacy controls for security.

System Architecture

The sign-to-communication process works like this:

Camera

↓

Hand Detection

↓

Hand Landmarks

↓

Sign Recognition

↓

AI / NLP Processing

↓

Context Detection

↓

Recognized Text

↓

Speech / Conversation

For the reverse communication:

Speech / Text

↓

Speech Recognition / Text Input

↓

AI Language Processing

↓

Intent & Context Detection

↓

Supported Sign Sequence

↓

3D Avatar

↓

Visual Sign Communication

Target Users

We designed AI SignBridge for people and places where communication accessibility is important.

Our possible users include:

Sign-language users

Hospitals and healthcare centres

Emergency service environments

Banks

Government offices

Educational institutions

Public-service centres

Accessibility-focused organizations

Families and caregivers

People learning supported sign vocabulary

Challenges We Faced

One of the biggest challenges we faced was making sign recognition work properly with camera input.

The result can change depending on lighting, camera angle, hand position, background and movement speed. Different people can also perform the same sign in slightly different ways.

Another challenge was making the communication more context-based instead of treating every sign as just one separate word.

Creating the 3D sign animations was also challenging because hand movement, position, timing and sequence all need to work together.

We also had to think about how to make the interface accessible while keeping it simple and easy to use.

Privacy was another important part because our project works with camera and microphone input.

Accomplishments We Are Proud Of

We are proud that we were able to bring different technologies together into one project.

Some of our main accomplishments are:

Two-way communication

AI-assisted sign recognition

Camera-based interaction

3D sign-language avatar

Context-specific service modes

Emergency communication mode

Two-person conversation mode

Practice mode

Multilingual interface

Accessibility features

Privacy-focused design

Expandable sign vocabulary

The main thing we are proud of is that our idea grew from a simple sign translator into a communication platform that can be used for different real-life situations.

What We Learned

While working on AI SignBridge, we learned that creating an AI project is not only about connecting an AI model.

We learned about:

Computer Vision

Hand Landmark Detection

AI and NLP

Speech Recognition

3D Animation

Real-Time Web Applications

Accessibility

Privacy

API Integration

Database Architecture

Cloud Deployment

User-Centered Design

We also learned that AI has limitations. Instead of claiming that our system can translate every sign, we decided to work with a defined supported vocabulary and keep the project open for future improvements.

Impact

Our main aim is to reduce communication barriers for people who use sign language.

AI SignBridge can help make basic communication easier in places where the other person may not know sign language.

It can be useful for service interactions, emergency situations, learning and everyday communication.

The 3D avatar also gives another way to understand the response visually.

We are not trying to replace human interpreters. We want to provide an additional technology-based communication option that can be available when needed.

Future of AI SignBridge

We see AI SignBridge as a project that can grow much more in the future.

Right now, our main focus is on supported signs, text, speech and the 3D avatar. In the future, we want to add more signs and make the system understand longer sign sequences instead of only individual signs.

We also want to improve the accuracy of sign recognition so that it can work better with different people, hand positions, lighting conditions and backgrounds.

More Indian Sign Language vocabulary and more Indian languages can also be added so that the project can reach more users.

Another area we want to improve is the 3D avatar. We want smoother hand movements, better expressions and more natural sign sequences. Personalized avatars and better practice features can also be added.

In the future, AI SignBridge could also be connected with hospitals, banks, government offices, colleges and public-service centres.

We are also interested in offline or on-device AI so that some features can work even when internet connectivity is poor. Wearable devices and other assistive technologies can also be explored.

Our idea is not to stop with the current prototype. We want to keep improving the recognition, vocabulary, languages, animations and accessibility features based on real user feedback.

Our future goal is to make AI SignBridge a simple and useful communication bridge that helps more people communicate comfortably without feeling limited by communication barriers.

Why AI SignBridge Matters

Communication is not just about speaking words. It is about understanding, responding and being understood.

We created AI SignBridge because we wanted to use technology to make communication easier for people who use sign language.

By combining AI, computer vision, speech technology, NLP and 3D animation, we are trying to build a communication bridge that can be useful in everyday situations as well as places where communication is very important.

Our vision is simple:

Make communication more accessible, especially when it matters most.

Project Highlights

Project: AI SignBridge

Tagline: Communication Without Barriers

Core Technologies: AI, Computer Vision, NLP, Speech Processing and 3D Animation

Communication: Sign ↔ Text ↔ Speech

Main Focus: Critical-Service Communication

Main Innovation: Two-way communication with context-based features and an interactive 3D sign-language avatar.