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  "document": {
    "abbrevTitle": "SMPTE Mot. Imag. J",
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      "source": "parsed",
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      "version": "smpte-idams-publication@v1"
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    "abstract": "A novel quality assessment system design for closed captioning (CC) is proposed. CC was originally designed to serve hearing-impaired audiences. Traditional quality assessment models focus on empirical methods only, measuring quantitative accuracy by counting the number of word errors in the captions for a segment. However, hearing-impaired audiences have been outspoken about their dissatisfaction with the quality of current CC. One solution to this problem may involve inviting human evaluators, who represent different groups, to assess the quality of CC at the end of each segment, but in reality, this may be difficult to do and very labor-intensive. To solve this challenge, we propose the training and use of an artificial intelligence system to predict subjective CC quality based on human assessment data. In this paper, the design and development process, to be used in developing this system, is described.",
    "abstract$meta": {
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      "source": "parsed",
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      "version": "smpte-idams-publication@v1"
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    "authors": [
      {
        "bio": "Somang Nam was born in Bielefeld, Germany, in 1989. He received an HBSc degree in computer science with a mathematics and music minor from the University of Toronto, Toronto, ON, Canada, in 2013, and the MSc degree in computer science from Ryerson University, Toronto, in 2016. He is currently a PhD candidate in industrial engineering with the University of Toronto. His main areas of research interest are human factors, human–computer interaction, and accessibility.",
        "name": "Somang Nam",
        "orcid": "0000-0002-7785-9003"
      },
      {
        "bio": "Deborah Fels received a PhD degree in human factors from industrial engineering with the University of Toronto, Toronto, ON, Canada, in 1994. She is currently employed as a professor with the Ted Rogers School of Information Technology Management, Toronto, and the director of the Inclusive Media and Design Centre at Ryerson University, Toronto. Her research interests involve inclusive design, access to media and technology for people with disabilities and older adults, and inclusive video game design and inclusive business. She has published over 150 articles on inclusive technologies and applications and received three patents. She is also a professional engineer.",
        "name": "Deborah Fels",
        "orcid": "0000-0001-7295-3386"
      },
      {
        "bio": "Mark Chignell received a PhD degree in psychology from the University of Canterbury, Christchurch, New Zealand, and a master’s degree in industrial and systems engineering from Ohio State University, Columbus, OH. He is a professor of mechanical and industrial engineering with the University of Toronto, Toronto, ON, Canada. He carries out research in human factors and user interface design, with particular interest in health care, aging, telecommunications, and driving applications.",
        "name": "Mark Chignell",
        "orcid": "0000-0001-8120-6905"
      }
    ],
    "authors$meta": {
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      "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
      "source": "parsed",
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      "version": "smpte-idams-publication@v1"
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    "contentType": "orig-research",
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      "confidence": "high",
      "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
      "source": "parsed",
      "updated": "2026-10-07T17:09:33.718Z",
      "version": "smpte-idams-publication@v1"
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    "copyright": {
      "holder": "SMPTE",
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        "confidence": "high",
        "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
        "source": "parsed",
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        "version": "smpte-idams-publication@v1"
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      "year": "2021",
      "year$meta": {
        "confidence": "high",
        "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
        "source": "parsed",
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        "version": "smpte-idams-publication@v1"
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      "confidence": "high",
      "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
      "source": "parsed",
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      "version": "smpte-idams-publication@v1"
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    "docId": "10.5594-JMI.2021.3059344",
    "docId$meta": {
      "confidence": "high",
      "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
      "source": "parsed",
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      "version": "smpte-idams-publication@v1"
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    "docLabel": "SMPTE Motion Imaging Journal ( Volume: 130, Issue: 3, April 2021)",
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      "confidence": "high",
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      "source": "parsed",
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      "version": "smpte-idams-publication@v1"
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    "docTitle": "Toward a Subjective Assessment System for Closed Captioning Quality",
    "docTitle$meta": {
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    "docType": "Journal Article",
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    "href": "https://doi.org/10.5594/JMI.2021.3059344",
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    "issn": {
      "electronic": "2160-2492",
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      "print": "1545-0279",
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        "confidence": "high",
        "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
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    "issn$meta": {
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    "journalAcronym": "MIJR",
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    "journalTitle": "SMPTE Motion Imaging Journal",
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      "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
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    "keywords": [
      "Artificial Intelligence",
      "Neural Network",
      "Captions",
      "Machine Learning",
      "User Centered Design"
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    "keywords$meta": {
      "confidence": "high",
      "note": "Ingested from SMPTE IDAMS <publication> (_source/SMPTE/Journal Article Repository/2021/7261654/9395650/09395669.xml) via idamsIngest.js",
      "source": "parsed",
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      "version": "smpte-idams-publication@v1"
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    "number": "3",
    "number$meta": {
      "confidence": "high",
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      "source": "parsed",
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    "pages": "35–44",
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      "confidence": "high",
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    "publicationDate": "2021-04-01",
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    "publisher": "SMPTE",
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