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.
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.
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 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.
When average TV viewers are channel surfing on the couch, they probably aren’t thinking too much about big data. But it’s already beginning to shape the viewing experience, namely by providing recommendations. And as time goes on, it will begin to have an even bigger impact.
As the amount of video content—and video viewers—grows, so does the data available about viewing habits and preferences. This is a boon for content creators, who can begin to leverage these insights to create better experiences for their customers in a variety of different ways. While there’s still a lot of data left to be uncovered, changes are already underway in the realms of service quality, content recommendation and production.
For more details on the topic of using data for video enrichment, also be sure to read this Uncovering Dark Video Data with AI white paper.
In the past few years, there has been a major shift towards video content as the primary form of media. Considering this momentum, the importance of closed captioning has only increased. However, delivering closed captions at scale is challenging for media and entertainment companies—they are costly to create, and the manual undertaking can be burdensome to production teams. Surrounding all of this is also the ever-changing compliance landscape, wherein adapting closed captions to meet regional or industrial guidelines can be tricky.
Today, IBM has introduced Watson Captioning, a new standalone offering that helps to solve these challenges. Watson Captioning leverages AI to automate the captioning process, while ensuring increased accuracy over time through its machine learning capabilities. In turn, this saves businesses both time and money, and delivers a scalable solution. Watson Captioning is a customizable offering that provides flexibility and productivity, can be easily managed across compliance standards, and has the potential to transform industries beyond media and entertainment.
By 2021, video is expected to comprise 82 percent of all global internet traffic. For the web audience, expectations of high-quality, personalized content are rising, too.
Many streaming video companies have been looking to artificial intelligence to meet the changing needs of their audience. And, according to David Kulczar, senior product manager of Watson Video Analytics at IBM Watson Media, that trend will continue in a big way, shaping streaming video trends 2018.
We sat down with Kulczar to get his predictions for how widespread the industry’s adoption of cutting-edge technologies will be in the coming year.
For all the great strides that live streaming video has made in the 21st century, the captioning process has remained largely stuck in the past. Humans still do the heavy lifting by manually typing captions word by word. Captioning pre-recorded video can take up to 10 times longer than the video itself — and the challenge is even greater with live video, which offers no time for review.
It’s not only clunky and labor intensive — it also can be costly. In fact, many companies agree that budget constraints are one of the top barriers to captioning.
But for full-service video production companies like Suite Spot, manual captioning, arduous as the process may be, still remains the quickest and most accurate way to meet clients’ captioning needs.
That may change soon though, according to Suite Spot Co-Founder Adam Drescher. Automated captioning technology is maturing fast, he notes, and even may be poised to disrupt the entire video industry in the near future. Case in point: IBM Cloud Video recently introduced the ability to convert video speech to text through IBM Watson.
When Juan Martin del Potro faced Dominic Thiem on Day 8 of the US Open, die-hard tennis lovers might have been excited, but it didn’t have the hallmarks of a “must see” event for casual fans. Few expected del Potro, ranked 24th, to advance.
But when he staged one of the best comebacks in US Open history, everyone wanted to see how it was done. And within minutes, they were able to, thanks to IBM Watson powering US Open 2017 highlights.
Watson assembled a clip reel within five minutes of the end of every match at this year’s Open, making highlights and key moments available to fans two to 10 hours more quickly than during previous years. The event marked the official launch of IBM Watson Media, a new business unit that leverages Watson’s leading AI capabilities to meet the future needs of broadcasters and their audiences.