Demand and associated costs  for note-taking supports for students with disabilities are increasing around the world.  Institutions that use volunteer notetakers benefit from low costs, but do not necessarily provide equity of access.  Institutions that use professional services  face astronomical costs, but provide better accessibility.   The tension between quality (accessibility) and costs underscores the importance of articulating a business case to support speech recognition based educational transcription.

A project team is exploring innovative business models that could enable individuals and organizations to efficiently access speech recognition based transcription of educational content.  Initially the focus is narrowed to two applications:

  1. automated transcription of recorded lectures to produce multimedia transcripts
  2. automated captioning of recorded educational media (video, modules, etc)

 

Key activities include:

  • reviewing macro level technological, demographic, social, and educational factors that could affect the business case
  • analyzing the competitive landscape of traditional captioning and transcription solutions and services
  • defining fixed and variable costs associated with speech recognition based captioning and transcription solutions
  • collecting data on current costs for captioning and transcription services