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Live CaptioningACMA Citizen Conversation Forum15 September 2015Tony Abrahams
Chief Executive Officer
ai-media.tv | ai-live.com | visibleclassroom.com
The current situation gives
no overall visibility
Legislation is currently driving our behaviours
But viewers do not get an overall quality picture.
Mistakes will ALWAYS occur.
Reviewing viewer complaints are insufficient to assess overall quality.
So how do you assess quality?
First, we need to recognise that not all errors are equal.
And a way to measure quality
We’ve adopted NER method for quality assessment.
N = number of wordsE = Editing errors (poor
captioner decision)R = Recognition
(captioner / software)
A lie
An error that the viewer can still follow
Omits a piece of information
Live captioners should only correct lies.
SUMMARY OF RESULTSScore
Correcting: “Hayes’s on his first one -- Hazelwood is on his first run” 0.25
Missed: “So we didn’t have that man who’s been there before. 0.5
Siddle hasn’t got a game. Four games in and Peter still hasn’t had a game.” 0.5
Second, some words are best left out.
We can be more transparent about how we are delivering real accuracy in captioning
Viewers want visibility into the service as a whole.
An audit approach to focus on what’s important
Two Clear Metrics: Uptime & Quality
Co-operation between broadcaster, provider and auditor
Q&A