Furthermore, the errors were classified into two major groups.
Among the four subcategories, namely omission, addition, substitution, and word order, substitution recorded the highest amount of errors with 357 cases (77.6%). The second is verbs with 93 cases (20.2%), then prepositions with 37 cases (8.1%). Among the different error categories, nouns record the highest number with 144 cases (31.3%). Upon completion of the analysis, it was discovered that the frequency of errors in each speech ranged between 10 and 46 cases, with an average of one error occurring about every 26 seconds. All the captioned errors were collected and analyzed. Only the first 10 minutes of the speeches were utilized for this investigation. The researchers selected ten male and ten female icons. These speeches were presented over a period of 12 years by speakers from different walks of life. The aim of this paper is to identify and analyze errors in the auto-generated captions of 20 commencement speeches on YouTube. However, at times they fail to contain accurate captions. Volume 17 Number 1, Spring 2020, Pages 1-318Īn Analysis of the Errors in the Auto-Generated Captions of University Commencement Speeches on YouTubeĪuto-generated captions on YouTube have proven useful in helping viewers better understand the words being spoken.
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