Speech-to-Sign Language Translation

Project Overview:

Objective

The objective of this project is to develop a robust speech-to-sign language translation system that can convert spoken language into sign language in real-time. This system aims to bridge communication gaps between the deaf and hearing communities, enabling more inclusive and effective communication.

Scope

The project involves creating a comprehensive dataset of spoken language and corresponding sign language gestures, training machine learning models, and developing a user-friendly interface for real-time translation.

Sources

Spoken Language Recordings: Collecting audio recordings of various languages and dialects, covering a wide range of topics and contexts.
Sign Language Gestures: Capturing video recordings of sign language interpreters or native sign language users signing the spoken language sentences.
Deaf Community Collaboration: Partnering with deaf individuals and sign language experts to create authentic sign language annotations.

Data Collection Metrics

Total Audio Recordings: 10,000 sentences
Total Sign Language Gesture Recordings: 10,000 sentence

Annotation Process

Stages

Audio Transcription: Transcribing spoken language recordings into text.
Sign Language Annotation: Annotating video recordings with corresponding sign language gestures.
Model Training: Developing machine learning models that can map spoken language text to sign language gestures using the annotated data.

Annotation Metrics

Audio Transcriptions: 10,000 sentences
Sign Language Annotations: 10,000 sentences

Quality Assurance

Quality Control
Implementing a validation process involving deaf community members and sign language experts to review and verify the accuracy of sign language annotations.
User Feedback
Collecting feedback from deaf individuals and sign language interpreters to continuously improve the translation system’s accuracy and usability.

QA Metrics:

Annotation Validation Cases: 2,000 (10% of total)

Conclusion

The Speech-to-Sign Language Translation project represents a significant advancement in inclusive communication technology. By combining a robust dataset, accurate annotations, and user feedback, this project aims to create a powerful tool for bridging the communication gap between the deaf and hearing communities, enhancing accessibility and promoting inclusive communication worldwide.