![]() ![]() has a speaker whose speaking style often involves repetition of some phrases (although interestingly the phrase “this means” was correctly picked up once by the automatic craptions but on the second occasion it was “this Maine’s”!).has good quality audio and it doesn’t have any background noise or sound effects and / or music.only has a single speaker, who speaks clearly and in a slow, consistent, monotonic and deliberate manner.This YouTube video was chosen as it represents the best possible chance for Google and YouTube to “get it right” using their voice recognition and deep neural language processing (NLP) tools as it: This represents an error rate of 4.66% or more importantly, an accuracy rate of 95.34%! Memo to Google and YouTube - Don’t rest on your laurels just yet There should have been 236 words in total in the automatic craption file.Īnd there was only 11 errors (or rows colour coded as red) in the automatic craption file. Then I used a very simple calculation of accuracy (which completely ignores any errors in the timing and / or syncing of the captions). where Google and YouTube’s voice recognition and deep NLP tools got it wrong.ġ4 words side by side in the Auto CRAP and Correct CAPS columns with an error coded in red - that versus than. Red colour code = errors or differences between the auto craptions and the corrected captions. Note: Words that were coded as “Orange” were not treated as errors as they did not detract from my ability to comprehend the video. I did not treat these as errors in any way. Capitalization at the start of a sentence). fullstops at the end of a sentence) or grammar (i.e. Orange colour code = means that there is a difference between the two files but it’s usually just a matter of punctuation (i.e. Green colour code = no error or difference between the auto craptions file and the corrected caption file. Then I did some basic colour coding to score each word for accuracy on the simplistic basis of whether it was comprehensible to me (or not). Then I repeated this step in the adjacent column, entering in each word of the corrected caption file. I first created a Google Sheet and entered each word in the automatic craptions file in the first column. YouTube video screenshot showing Australia’s Prime Minister, Tony Abbott
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