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An Analysis of the Errors in the Auto-Generated Captions of University Commencement Speeches on YouTube

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  • 발행기관
    아시아영어교육학회 바로가기
  • 간행물
    The Journal of AsiaTEFL SCOPUS KCI 등재 바로가기
  • 통권
    Vol.17 No.1 (2020.03)바로가기
  • 페이지
    pp.143-159
  • 저자
    Jeong-Hwa Lee, Kyung-Whan Cha
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A372123

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원문정보

초록

영어
Auto-generated captions on YouTube have proven useful in helping viewers better understand the words being spoken. However, at times they fail to contain accurate captions. In these cases, they lead to confusion. The aim of this paper is to identify and analyze errors in the auto-generated captions of 20 commencement speeches on YouTube. These speeches were presented over a period of 12 years by speakers from different walks of life. The researchers selected ten male and ten female icons. Only the first 10 minutes of the speeches were utilized for this investigation. All the captioned errors were collected and analyzed. 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. Among the different error categories, nouns record the highest number with 144 cases (31.3%). The second is verbs with 93 cases (20.2%), then prepositions with 37 cases (8.1%). Among the four subcategories, namely omission, addition, substitution, and word order, substitution recorded the highest amount of errors with 357 cases (77.6%). Furthermore, the errors were classified into two major groups. The first, involving function words, appeared in 169 cases (36.7%). The second, involving content words, appeared in 291 cases (63.3%). The results of this research suggest that a continuous development of the voice recognition software that automatically generates captions is necessary for more efficient and accurate data that will help viewers and listeners better comprehend the video contents.

목차

Abstract
Introduction
Literature Review
Auto-generated Caption Errors
Machine Translation Errors
Method
Data Collection
Data Analysis
Results
Auto–Generated Caption Errors Based on 10 Categories and Four Sub-Categories
Function Word and Content Word Errors
Frequency Rates of Auto-generated Caption Errors as Recorded from the 20 Commencement Speeches
Discussion and Implication
Relating to the 10 Categories and Four Sub-Categories
Relating to Function Words and Content Words
Relating to the Frequency Rates of Each of the 20 Commencement Speeches
Summary and Limitations
Acknowledgments
The Authors
References
Appendix A
Appendix B

키워드

auto-generated caption errors YouTube university commencement speeches function words content words omission addition substitution word order

저자

  • Jeong-Hwa Lee [ Hansung University, Korea ]
  • Kyung-Whan Cha [ Chung-Ang University, Korea ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    아시아영어교육학회 [Asia TEFL]
  • 설립연도
    2004
  • 분야
    사회과학>교육학
  • 소개
    The goals of Asia TEFL are to promote scholarship, disseminate information, and facilitate cross-cultural understanding among persons concerned with the teaching and learning of English in Asia. In order to accomplish this, Asia TEFL will pursue the following goals: 1. To link ELT professionals in joint research on issues and concerns regarding English teaching and learning in the Asian context. 2. To publish an academic journal, The Asia TEFL Journal, as an internationally recognized journal in the field of English language teaching. 3. To host conferences and seminars addressing important issues concerning ELT in Asia. 4. To develop proficiency guidelines and assessment methods designed for the needs of the Asian context. 5. To develop programs for Asian learners and teachers of English to build their English language proficiency and cultural understanding and provide them with the skills required to be efficient English teaching professionals.

간행물

  • 간행물명
    The Journal of AsiaTEFL
  • 간기
    계간
  • pISSN
    1738-3102
  • eISSN
    2466-1511
  • 수록기간
    2004~2026
  • 등재여부
    SCOPUS,KCI 등재
  • 십진분류
    KDC 740 DDC 420

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