Welcome to
Media Captioning Services

The most reliable Closed-Captioning Company in United States


Welcome to
Media Captioning Services

Over 30 years of Captioning Real-Time News


Welcome to
Media Captioning Services

over 1,042,000 hours of national and local programming captioned since 1987

About Us

MCS, as we are also known, was formed in 1987 by Patricia Ferrier of Los Angeles, and was the first woman-owned Closed Captioning Company formed in the U.S. It remains the largest privately held woman-owned Closed Captioning company in the U.S.

Real-Time Closed Captioning

Real-Time Captioning is the process of creating text from the audio or speech track of television broadcasts and streaming video as it occurs.

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Order MCS Captions

If you are interested in choosing MCS for your real time closed captioning needs, please use the following form.

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MCS has captioned over 1 million hours while addressing any technical issues that can occur in the captioning.

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What Is Closed Captioning?

Closed captioning is an assistive technology that allows the deaf and hard of hearing to comprehend video content.

Real-Time or Offline?

Real-Time is typically used in network broadcasts to maintain accuracy and flexibility. Lately Real-Time has extended to Live Stream Captioning over Twitter, Facebook, ect.  Offline content is typically captioned when the content will be used for purposes outside of a broadcast or streaming.

Laws and Regulations

Choose from the links below to learn more about the laws and regulations governing the implementation of Closed Captioning

FCC Quality Guidelines Document.

How to Order Internet Captioning

Use CYBERSCRIPT™ services for your internet captioning events. Contact us at 888-777-3966 for further information.

A.I. Vs Real Time Captioning

Recent advances in the field of artificial intelligence spurred by developments in neural network research, computer processing power, and in some respects, the internet, have given rise to myriad speculation about applications for this technology in speech-to-text.

Although advances have been impressive, current automated speech-to-text systems are failing to produce better than 90% accuracy on even the most common turnkey transcription or speech-to-text applications, at least from commercially available systems. Cognitive resolution of words to produce accurate replication of speech to text is still elusive, and still awaits further advances in neural network/cognitive recognition by these computing systems.

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