Our human corrected captioning service

Our hardworking team of student interns correct machine-generated captions and transcripts for priority content.

How quickly are captions corrected?  

When you submit a request, you will be notified via email and can check the progress of the task in Microsoft Teams/Microsoft Planner. It may take a few days to a few weeks depending on the length of the content and the priority compared to other requests. You can read about how we prioritise caption correction below.       

How do we prioritise caption correction? 

Each week during semester times, around 190 hours of content are uploaded to Media Hopper Create, and 1,230 hours of lectures are recorded on Media Hopper Replay. Everything is automatically machine-captioned, but our part-time interns cannot correct it all, it would take too long. Help us find the media which is not accessible to you or your audience by submitting a request.  

Prioritisation criteria:

1: Schedule of AdjustmentsIf your request is for accurate captions as part of a Schedule of Adjustments through the Disability and Learning Support Service. 
 
e.g.: Automatically recorded lectures on a course (Media Hopper Replay), tutor-created videos in Media Hopper Create, etc. 
2: Public Facing

If your Media Hopper Create content is aimed towards the general public. 

 
e.g.: Open day ceremonies, graduation speech, welcome instructions for new students, conference keynote speeches, inaugural lectures, featured lectures, memorial lectures, Gifford lectures, etc. 

3: Everything else

All other content. 

During busy times, we may have to lower priority.  

Request caption correction by filling out the short Form linked above, or contact us at captions@ed.ac.uk for general enquiries. 

 

Automation, accuracy, and advice

Since 2019, the Captioning Service has employed motivated and competent student interns from all three colleges on a part-time and flexible basis. Our captioners gain valuable experience in a positive and dynamic working environment, and they find the role meaningful and purposeful. 

We do more than correcting captions: 

- We perform detailed accuracy tests on machine-generated transcripts to make sure they are good enough. 

- We update the Captioning Style Guide regularly with examples and advice. 

- We maintain a database on which we are testing our AI-enhanced caption correction system, which we expect will allow us to increase the volume and quality of our work. 

 

Guidance and training on correcting captions on your own content. 

 

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