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TAG adds new language detection feature to closed captions and subtitles quality assurance

Contributed Content / Press Release

TAG Video Systems has developed a new Language Detection feature set to transform how operators ensure quality and compliance across large scale operations with multiple closed captions and language subtitles. Unveiled at the recent NAB 2024, this innovative technology offers much-needed automation and precision to the traditionally labor-intensive world of caption quality assurance.

The challenge of multi-language and large scale captions monitoring

While accurate and compliant captions are essential for a positive viewer experience, operators have long grappled with the complexities of ensuring captions meet the mark. This is particularly true in today’s content landscape, where video is consumed globally across multiple languages. TAG’s Language Detection feature aims to alleviate this burden.

The sheer scale of video content produced and distributed makes accurate caption monitoring an immense task. The resources required to manually track and analyze captions across multiple languages can be overwhelming. Additionally, relying on human operators introduces the potential for errors. Fatigue, distraction, and varying levels of expertise can all contribute to inconsistencies in caption quality, posing a challenge to compliance with accessibility regulations.

How it works

The core of this technology lies in its ability to automatically pinpoint the language of subtitles within video content. Powered by advanced algorithms, TAG performs a meticulous quality analysis informed by language-specific dictionaries, which in turn provides the data within the multiviewer output in the form of two parameters: identified language, and quality percentage against the identified language’s dictionary. The data can also be aggregated and visualized with data visualization tools to identify trends or centralize large scale operations. This significantly streamlines the caption monitoring process, offering these key benefits:

Frees Up Operator Time: By eliminating manual monitoring of closed captions and subtitles, operators gain valuable time to focus on more strategic and nuanced tasks.

  • Proactive problem solving: Real-time monitoring paired with helpful, informative alerts enables operators to quickly address any potential caption quality problems.
  • Pinpoint accuracy: Reliable language identification and quality measurement against a dictionary helps avoid human error and assure accuracy and compliance.
  • Quality that meets the mark: Language-specific analysis ensures captions uphold quality standards and regulations, ultimately enhancing the viewing experience.
  • Informed decision-making: Data visualization tools provide insightful overviews of caption/subtitles quality trends, empowering media operations to make strategic improvements.

“TAG’s Language Detection is a glimpse of the future of quality assurance” says Michael Demb, VP Product Strategy at TAG Video Systems. “Operators no longer need to watch and listen to every channel to deliver quality captions and subtitles. By automating crucial processes, we’re enabling them to focus on higher-level analysis and decision-making, ultimately ensuring a better experience for all viewers.”

Recognized for innovation

The impact of TAG Language Detection hasn’t gone unnoticed. The feature has already garnered significant recognition within the industry, taking home the following awards:

  • NAB Product of the Year 2024
  • Future’s Broadcast & Cable Best of Show 2024

The future of caption quality assurance

TAG Video Systems’ Language Detection feature marks a new era in quality assurance. By injecting automation and precision, it promises to reshape how operators approach this crucial aspect of media production and delivery. As the demand for accurate and accessible multi-language content continues to rise, this technology is poised to become an indispensable tool for ensuring a seamless and inclusive viewing experience for audiences worldwide.

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