How Live Captioning Improves Accessibility

The primary benefit of live captioning is that it makes audio content accessible for individuals who are deaf or hard of hearing. It also helps people who have no hearing impairments but need to read captions for various reasons. This article covers the different ways live captions are produced and delivered.

What Access Means in Live Captioning

Some of the situations in which live captions are useful for anyone include watching live video on a device without earphones in a quiet environment, such as a library, or on TV displays in a noisy place, such as a bar.

Live captions are increasingly used in other settings, like corporate or educational online meetings, improving overall inclusivity and communications. However, the quality of live captions might vary greatly depending on multiple factors, including human participation. These are some of the most common ways in which live captions are created:

1. Automatic live captioning: This process relies on automatic speech recognition (ASR) to transcribe spoken words into text in real time. ASR systems use algorithms that analyze audio input and generate captions with impressive speed and efficiency. However, the accuracy of ASR captions varies depending on things like audio quality, speaker accents, and background noise. Human participation may be required to correct errors and ensure caption quality.

2. Human live captioning: In this workflow, trained stenographers/subtitlers transcribe spoken words into text in real time using specialized keyboards or software. This is the sort of work done at court, for example, where verbatim captions are necessary. The expectation is that these captions will be highly accurate but will be produced with a slight delay (lag time) due to the time required for manual transcription.

3. Respeaking plus live captioning: In this process, ASR and human captioning combine to create more accurate captions during live events. Respeaking means that a human (a respeaker) listens to the audio and repeats the spoken words clearly into a speech recognition system, which then generates or re-generates the captions (more on that below). The purpose of this process is to improve accuracy compared to ASR captioning alone. Trained respeakers can enunciate words and filter out background noise without creating significant delays.

Respeaking is considered a “hybrid approach” to live captioning. It can be done in the same language as the original audio, as is the case for major broadcasting companies around the world for live events (intralingual) or include a translation step to produce live captions in other languages (interlingual).

Other ways to obtain interlingual captions are to simply go from ASR to machine translation or to use speech-to-speech translation and then ASR. However, there may be errors in the final captions, so a human might still be involved to make corrections as the machine translated and/or transcribed text is produced.

The main advantage of using respeaking in live captioning is the combination of the speed and affordability of ASR with the accuracy of human captioning. This is a good solution for settings with challenging audio conditions and content with complex terminology.

How AI Gives Automated Live Captions a Boost

AI-enabled speech recognition offers a way to level up transcription in real time. This cost-effective technology can be particularly useful in settings like corporate online meetings and virtual classroom lectures.

AI ASR systems can be easily integrated into existing video conferencing platforms or used as standalone solutions. Also, depending on the type of event being captioned, a human corrector might not be needed. This makes live captioning more accessible for low-budget productions and content with simple vocabulary.

AI-enabled speech-to-text technologies are successfully used in various live captioning applications, including news broadcasts, weather reports, sports events, and live streams of all kinds.

These AI technologies also offer improved accuracy (compared to previous versions of ASR), handling of diverse accents and dialects, better punctuation and capitalization, and integration with other accessibility features. AI is also a path to increased accessibility as demand for live captioning increases across entertainment, educational, and corporate platforms.

One challenge users face is deciding whether or not to involve a human to correct errors in real time. This has cost implications: on the one hand, there are savings from automation, but on the other hand there are costs associated with involving professionals to correct text in real time.

When considering which process to use for live captioning, users are advised to take the following into account:

• Budgets

• Accuracy requirements (level of risk)

• Complexity of content (e.g., terminology)

• Speed needs (consequences of any lag)

• Scalability (volume of content, language involved)

Generally speaking, AI ASR is a good option for low-budget, simple content with good audio quality. Human live captioning is best when verbatim captions are needed, such as broadcasts of court proceedings, or situations where anything less than high accuracy presents a risk.

With live captioning, there is always a risk of accuracy errors and overall lower quality than captions added offline. Regular AI-assisted transcription and subtitling includes the careful eye of an expert to ensure accuracy and other elements, such as synchronization and timing for multilingual cases, are properly handled.

Respeaking can be a good compromise between cost and accuracy, and may be suitable in challenging audio conditions or complex content. In any of the scenarios involving AI, automated speech to text helps make the live captioning process easier, faster, and more budget-friendly, but the quality will always be superior in offline captions reviewed by an expert.