Sign language is a visual language used by deaf people as their primary means of communication. Unlike spoken languages, sign language conveys thoughts using hand shapes, body movements, and facial expressions. It is essential for deaf people to have access to sign language for their social, emotional and linguistic growth.
Different regions use different sign languages:
- American Sign Language (ASL) - USA
- British Sign Language (BSL) - Britain
- Indian Sign Language (ISL) - India
Indian Sign Language (ISL) uses:
- Manual signs: One-handed and two-handed signs using hands.
- Non-manual signs: Facial expressions and body posture changes.
Goals
The project aims to enable deaf individuals to access information and services by translating speech into Indian Sign Language (ISL), capturing ISL gestures and expressions for effective communication.
System Architecture and Technical Specification
The system captures user audio, which the Automatic Speech Recognition (ASR) module converts into text. The text is then processed by the Sign Language Generation module, where machine learning models map it to corresponding sign sequences. Finally, the signs are displayed visually via an avatar or signing interface for the deaf user.
This system leverages Artificial Intelligence (AI), Machine Learning (ML) and Natural Language Processing (NLP):
- AI enables tasks like speech recognition, language translation, and visual rendering.
- ML allows the system to learn from ISL datasets and predict accurate sign outputs.
- NLP analyses sentence structure and prepares text for correct ISL grammar conversion.
Platform and Tools
- Programming Language: Python (preferably 3.x)
- IDE: PyCharm Community Edition
- Operating System: Linux (Ubuntu recommended)
- Libraries: PyAudio, Google Speech API, NLP libraries
- Data Sets: Publicly available ISL/ASL datasets from research sources and open repositories.
Methodology
- Audio Input: Capture audio using the PyAudio module from a microphone.
- Speech-to-Text Conversion: Use Google Speech API to convert audio into text.
- Dependency Parsing: Analyse grammatical structure and relationships between words to prepare the sentence for ISL grammar conversion.
- ISL Generator: Convert the text into ISL using ISL grammar rules.
- Sign Language Output: Display the generated ISL using a signing avatar.
Advantages
- Helps the deaf community communicate independently.
- Provides scalable solutions for education and social interaction.
- Can be extended to other languages and sign systems.
Future Scope
- Interpreter Replacement: Reduce reliance on human interpreters for everyday communication.
- Facial Expressions & Body Language: Include non-manual signs for better contextual understanding.
- Mobile and Web Application: Extend reach to more users via mobile and web platforms.
- Two-Way Communication: Integrate hand gesture recognition using computer vision for interactive communication.