How Closed Captioning is Enabled by ASR

There are many different ways that closed captioning is enabled by speech-to-text and automatic speech recognition (ASR). In this blog post, we'll discuss some of the most common of these use cases, including creating captions for live events, podcasts, and transcribing videos. We'll also explore the benefits that state-of-the-art, AI-powered speech-to-text solutions like Deepgram can provide to closed captioning companies. But before we start, let's define what exactly closed captioning is.

Closed captioning is a means of adding a transcript of what is said to video files. It's similar to subtitles, but while subtitles are usually intended for someone who doesn't speak or understand the language used in the video, closed captions are intended for those who might be deaf or hard of hearing. However, Verizon Media found that 80% of closed caption users aren't hearing impaired, so this is a feature that's expanding in use. And, in case you're curious-"closed" here means that the captions aren't visible to the viewer until they turn them on.

It might seem like there's just one use case for ASR in closed captioning-namely, providing a transcript of what was said-but we can think about several different domains where captions can be generated with speech-to-text solutions, and that have real advantages over using human transcriptionists.

Speech-to-text for live captioning is one of the prime use cases for ASR solutions. These captions are especially important for live events because they allow people who are deaf or hard of hearing to follow along with what is happening and be included in the event. And, these captions can also help others-those too far away from the speaker to hear clearly, for example, can also benefit. This type of captioning can be done with or without human intervention, but it's important to have someone who is familiar with ASR monitoring the captioning process to ensure accuracy.

Similar to live events, live television is another place where closed captions powered by AI speech-to-text can have a big impact. If you've ever tried to watch something live with closed captions turned on, you know that they're often delayed several seconds while humans transcribe what was said. But by using speech-to-text for captioning, transcriptions can be generated in real time, removing delays and lag.

Captioning can also be used to transcribe pre-recorded videos or podcasts. This is often done for educational or training videos, but it can also be used for other types of video content. ASR can be used to create a transcript of the video, which can then be used to create captions. This type of captioning is important for making sure that all viewers can access the information in the video, regardless of whether they are able to hear the audio.

Although you might mostly associate captions with video content, they're also a critical component of accessibility for podcasts. Podcast content has exploded in recent years and has become a major type of media. But it's one that can be difficult or impossible for people who are deaf or hard-of-hearing to access without captions. These captions can help other people, too-non-native speakers, people listening with background noise, and those who'd rather read content than listen to it, to name a few. You can read more about the importance of captioning for podcasts at Podcast Accessibility.