Streaming Video Blog

How does automated closed captioning work? What elements improve or impact the accuracy for artificial intelligence (AI) driven captioning?

This article examines why automating caption generation is important before diving into how speech recognition and other elements combine to provide an accurate experience. This includes many behind the scenes aspects that go into how AI approaches the task of transcribing audio. The article then concludes with a few tips to keep in mind when looking for a solution that automates closed captioning.

For more information on this topic, including how to succeed with automated closed captioning and what to expect, also be sure to download our in-depth How Can AI Elevate Your Closed Captioning Solutions? white paper as well.

• Why automated closed captioning is important
• How speech recognition and auto closed captioning works
• Tips for automating closed captioning

Looking for a way to speed up the generation of accurate captions? Interested in AI vocabulary training?

Earlier, IBM introduced Watson Captioning to generate captions for videos using speech to text. These captions could then be edited for accuracy, or to adhere to personal preferences. Those capabilities are being expanded with the addition of the ability for Watson to learn based on those edits or to be taught. As a result, this can speed up the process of accurate caption generation through removing previously repeated tasks.

Note that this feature for Watson to learn based on edits or to be manually taught is currently only available from the stand alone Watson Captioning solution. It is not currently available for Streaming Manager or Streaming Manager for Enterprise, although will be coming to those in the future.

• How Watson learns: AI vocabulary and context
• The advantage of training Watson
• Self-learning: automatically training Watson
• Manually adding words to Watson’s vocabulary
• Tips for training Watson

With the news moving at lightning speeds, consumers are more tuned into current events than ever while media companies are challenged to keep pace. Broadcast networks are under intense pressure to respond quickly to breaking news, world events, and sporting games in order to satisfy consumer demand for instant, quality digital experiences.

However, delivering accurate captions for live broadcast is both time and resource intensive for broadcast networks, given that production teams must manually transcribe live programming in real-time – which often leads to delayed or incorrect captions. To solve these challenges, IBM launched Watson Captioning – a flexible, scalable, closed captioning software solution that leverages AI to automate the captioning process and uses machine learning to improve accuracy over time. As outlined in this white paper, Captioning Goes Cognitive: A New Approach to an Old Challenge, Watson is bringing greater context to video assets while removing some of the challenge associated with closed captioning.

Through its Live Captioning functionality, Watson Captioning empowers closed captions for broadcast networks, unlocking value from live video content and optimizing the viewer experience. By accurately captioning live video content, broadcasters can provide premium experiences for local viewers, increase accessibility for the hearing-impaired community, and adhere to compliance standards.

One of our core tenants at IBM is to find and work with great partners who share our vision and values. The ecosystem is important. At Watson Media, we’re focused on bringing powerful portfolio of AI (artificial intelligence) video solutions to market. To meet the unique needs of our customers, Watson Media works with a number of partners to augment our solutions and build robust solutions that aid in driving efficiencies, delivering elevated video experiences and delighting consumers.

In media, context is everything: Just as a hand signal that means “V for victory” in one country may be incredibly offensive in another, what’s culturally acceptable in a television show in the U.S. may be verboten elsewhere around the world.

By flagging questionable content for media compliance, Watson not only saves time and costs, but opens up opportunities in new markets for content creators and broadcasters alike. For more information about how AI can save time and money with compliance, also be sure to  download IBM Watson Media’s ROI analysis paper: From AI to ROI: When playback means payback.