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MIJ 2026, Volume 135, Number 4 (pp. 16 to 24)
[ACTIVE]

Using Generative-AI Speech-to-Text Output to Provide Automated Monitoring of Television Subtitles

Metadata

Publisher
SMPTE
Doc Type
Journal Article
Content Type
Original Research
Abbreviated Title
SMPTE Motion Imaging Jour.
Volume
135, No. 4, pp. 16–24
Abstract
This paper describes a proof-of-concept approach to monitoring timing errors and word loss in TV subtitles. It reviews previous attempts at subtitle monitoring and the problems caused to viewers by subtitle timing errors and word loss. It then introduces the use of speech to text technology and the conventions in subtitling where repetition, non-speech content and errors can make the task of aligning the speech-to-text transcript to subtitles more challenging. The paper describes the approach taken to remove non-speech content from the subtitles and transcript, along with the complex and iterative natural language processing techniques devised to ensure a sufficiently accurate alignment between the two. It then gives examples of the ways in which the results are displayed and some sample results showing the scale of problems with subtitle quality, along with examples of 24-hour plots, which are a convenient way to identify issues across a large sample of data. The paper concludes by reviewing the limits of this approach in terms of accuracy and points out the need for human oversight.
Publication Date
2026-07-01
DOI
10.5594/JMI.2026/TZBT7663
ISSN
Print: 1545-0279 | Electronic: 2160-2492
Link
https://doi.org/10.5594/JMI.2026/TZBT7663
Author(s)
Michael Armstrong
Keyword(s)
Accessibility, Quality, Monitoring, Subtitles, Captions
Copyright
© 2026 SMPTE

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Michael Armstrong; Using Generative-AI Speech-to-Text Output to Provide Automated Monitoring of Television Subtitles, MIJ 2026, Volume 135, Number 4 (pp. 16 to 24); SMPTE, 2026. Available at https://doi.org/10.5594/JMI.2026/TZBT7663
Snippet:
Michael Armstrong; Using Generative-AI Speech-to-Text Output to Provide Automated Monitoring of Television Subtitles, MIJ 2026, Volume 135, Number 4 (pp. 16 to 24); SMPTE, 2026. Available at https://doi.org/10.5594/JMI.2026/TZBT7663

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Preview:
Michael Armstrong; Using Generative-AI Speech-to-Text Output to Provide Automated Monitoring of Television Subtitles, MIJ 2026, Volume 135, Number 4 (pp. 16 to 24); SMPTE, 2026. Available at https://doi.org/10.5594/JMI.2026/TZBT7663
Snippet:
<span class="citation">Michael Armstrong; <cite>Using Generative-AI Speech-to-Text Output to Provide Automated Monitoring of Television Subtitles</cite>, MIJ 2026, Volume 135, Number 4 (pp. 16 to 24); SMPTE, 2026. Available at <a href="https://doi.org/10.5594/JMI.2026/TZBT7663" target="_blank" rel="noopener">https://doi.org/10.5594/JMI.2026/TZBT7663</a></span>

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Michael Armstrong; Using Generative-AI Speech-to-Text Output to Provide Automated Monitoring of Television Subtitles, MIJ 2026, Volume 135, Number 4 (pp. 16 to 24); SMPTE, 2026
doi: 10.5594/JMI.2026/TZBT7663
url: https://doi.org/10.5594/JMI.2026/TZBT7663
Snippet:
<li>
Michael Armstrong; <cite id="bib-10-5594-jmi-2026-tzbt7663">Using Generative-AI Speech-to-Text Output to Provide Automated Monitoring of Television Subtitles</cite>, MIJ 2026, Volume 135, Number 4 (pp. 16 to 24); SMPTE, 2026
<span class="doi">10.5594/JMI.2026/TZBT7663</span>
</li>