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If the AI hasn’t been trained on what MaserHub is, though, it’s liable to try and transcribe it as “laser hub”, without realizing it’s a noun, a conjoined word and has the spelling of “maser” depending on how it was pronounced. For example, let’s say a report is going to talk about a new service called MaserHub. This is the process of literally teaching it new words. Now there are a variety of different ways that the AI can be trained to deliver more accurate captions. Through leaning on the robust learning capabilities of IBM’s Watson, content owners can effectively train the artificial intelligence so it will be equipped for the task of transcribing a specific broadcast. This is a category where Watson Captioning shines. This is achieved through extensive training of the AI. As a result, a lot of importance is placed on having the artificial intelligence generate highly accurate captions from the start. While this can produce flawless captions, it’s a luxury not available for live content. When doing on-demand captions, content owners have the luxury of going in to edit results after the fact. This process is scalable, allowing rigorous training to be used again and again to generate accurate captions for live content. These are then delivered as 608 captions live on the broadcast, allowing end viewers to watch closed captioned content live.
#Live closed captioning serial
This is then fed over IP or serial to a closed caption encoder, such as the EEG HD492. Both of these sources are then fed into Watson Captioning, live in the case of the video content and ideally at least 20 minutes in advance in the case of the story scripts.įrom this, Watson Captioning begins to generate a transcript using speech to text. There is also the story scripts, brought in through a service like iNEWS or MediaCentral. On the far left is the video source, brought in through HD-SDI.
![live closed captioning live closed captioning](https://images.squarespace-cdn.com/content/v1/5efa65b7ceecbe5357d4bc73/1597665378988-HH9ZE40XM7LQG1BCMDEX/subtitlesNEWSREV.jpg)
The high level workflow for live captioning for broadcasting is this: How scripts are used in automatic captioning.To learn more about automatic closed captioning, register for our Auto Closed Captions and AI Training webinar. This delivers a solution that can not only be highly accurate, but one that is both scalable and built for high availability. For accuracy, the AI can be trained in advance, expanding both vocabulary and relevant, hyper-localized context through providing corpus. For the on-premise component, the Watson Live Captioning RS-160 is hardware created specifically for this use case by the Weather Company to complement the Captioning service. This uses a combination of artificial intelligence in the cloud and hardware on location. IBM Watson Captioning offers a service for broadcast television to caption their live content.
![live closed captioning live closed captioning](https://444vno15v5re20btub322y5h-wpengine.netdna-ssl.com/wp-content/uploads/2019/06/Live-Closed-Captions-iOS-instructions-1024x576.jpg)
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