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.

Speech-to-Sign Language Translation
Speech-to-Sign Language Translation
Speech-to-Sign Language Translation
Speech-to-Sign Language 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.
case study-post
Speech-to-Sign Language Translation
Speech-to-Sign Language Translation

Data Collection Metrics

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

Annotation Process

Stages

  1. Audio Transcription: Transcribing spoken language recordings into text.
  2. Sign Language Annotation: Annotating video recordings with corresponding sign language gestures.
  3. 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
Speech-to-Sign Language Translation
Speech-to-Sign Language Translation
Speech-to-Sign Language Translation
Speech-to-Sign Language Translation

Quality Assurance

Stages

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.

Technology

Quality Data Creation

Technology

Guaranteed TAT

Technology

ISO 9001:2015, ISO/IEC 27001:2013 Certified

Technology

HIPAA Compliance

Technology

GDPR Compliance

Technology

Compliance and Security

Let's Discuss your Data collection Requirement With Us

To get a detailed estimation of requirements please reach us.

Scroll to Top