Our Approach

We collect speech samples from volunteers who stutter, ensuring data privacy and ethical compliance. Each sample is analyzed and annotated by certified speech-language pathologists. Our methods adhere to international research ethics standards with approvals obtained from the participants.

Key Objectives

  • Develop an AI-based system to automatically detect and assess stuttering severity.
  • Build and expand an annotated database of speech samples from people who stutter.
  • Validate AI models through clinical collaborations.

Impact

  • Provides real-time stuttering severity analysis.
  • Enhances speech therapy treatment precision.
  • Contributes to global research on communication disorders.
  • Facilitates clinical trials for pharmaceutical research.

Methodology

📊 Data Collection

  • Audiovisual samples of Arabic & English speech from stuttering individuals.
  • Manual annotation by speech-language pathologists.

🤖 Model Development

  • Initial AI models trained on annotated data.
  • Continuous improvement through machine learning iterations.

✅ Validation & Impact Assessment

  • Comparing AI-generated assessments with human expert ratings.