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What is better? Automated or Human-Generated Closed Captioning?

Creating live captions can be accomplished through two main methods: human stenograph operators and automated Automatic Speech Recognition (ASR) technology. Each approach has its own set of pros and cons. In this article, we will try to break down the advantages and disadvantages of using one method compared to the other.

Human Stenograph Operators:


  1. Accuracy and Context: Human stenographers are skilled professionals who can capture spoken language with a high level of accuracy, including capturing nuances, accents, and context. They can also understand and adjust for homophones (words that sound the same but have different meanings) based on the context of the conversation.

  2. Adaptability: Stenographers can adapt to difficult audio conditions, such as background noise or multiple speakers, and make real-time adjustments to ensure accurate captions.

  3. Real-time Corrections: Stenographers can make corrections on the fly if they mishear something or if there's a need for clarification, ensuring that the captions remain accurate.


  1. Cost: Human stenographers are skilled professionals, and their services can be expensive due to the specialized training and equipment required.

  2. Fatigue: Stenographers can experience fatigue during long sessions, which might lead to a decrease in accuracy over time.

  3. Availability: Finding and scheduling qualified stenographers can sometimes be a challenge, especially for events that require captions on short notice.

Automated ASR (Automatic Speech Recognition) Technology:


  1. Cost-effective: Automated ASR technology is generally more cost-effective compared to hiring human stenographers, especially for long-duration events.

  2. Real-time Output: ASR systems provide captions in real-time, which can be useful for live events and broadcasts.

  3. Consistency: ASR systems maintain consistent performance regardless of session length, avoiding the fatigue that can affect human stenographers.

  4. Rapid Deployment: ASR technology can be quickly deployed, making it suitable for situations that require immediate captioning.


  1. Accuracy: While ASR technology has improved significantly, it still might not achieve the same level of accuracy as human stenographers, particularly in cases of accents, dialects, or complex language.

  2. Contextual Understanding: ASR systems may struggle with capturing contextual cues, leading to misinterpretations of words or phrases.

  3. Technical Challenges: ASR systems can be sensitive to audio quality, background noise, and multiple speakers, which could result in lower accuracy in challenging environments.

  4. Limited Vocabulary: ASR systems might struggle with uncommon or domain-specific terminology that is not part of their training data.

In summary, the choice between human stenograph operators and automated ASR technology depends on the specific needs of the situation. If accuracy and context are critical, and the budget allows, human stenographers might be the preferred choice. If cost-effectiveness, rapid deployment, and relatively good accuracy are the main priorities, automated ASR technology could be a more suitable option. Often, a combination of both approaches might be used to balance accuracy and cost considerations.

At Videolinq, we support both methods to create closed captioning. We are integrated with the leading captioning tools most stenograph operators use, and we offer automated closed captioning services.

  • Human Captioning: Ask your steno operator to use one of our partners, connect to Videolinq, and publish closed captioning to your live stream channel. Videolinq will sync the captions to the video and help you distribute the video + closed captioning to up to 25 target destinations.

  • Automated Captioning: Use EDIT, a real-time editor, to improve the accuracy of ASR technology. Correct mistakes generated by the AI-based automated closed captioning service. When the broadcast ends, export SRT/VTT captions files and transcripts in PDF format.

Interested in learning how to use Videolinq to create native or translated closed captioning and translations to video? Book a demo.


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