Voice Recognition Software vs. Human Transcription Services

Written by Kevin Liew on 30 Jul 2020
53,763 Views • Miscellaneous

Many multimedia content producers need transcription services to provide captions for their video materials. Transcription service providers either use human transcriptionists or voice recognition software. Both types have their pros and cons.

There is no doubt that human transcription provides the highest level of accuracy, but developers of voice recognition software continue to improve its features using the advancements in technology.

Many clients ask about voice recognition because it is becoming quite popular. Furthermore, it is a lot cheaper than human transcription. Let us compare the two so you can make the right decision on which type you want to use for your next transcription project.  

Using voice recognition software

Although most of the voice recognition software today is much better than that available a few years back, there are still issues with accuracy, quality, and the time spent in the transcribing process. Large artificial intelligence (AI) companies such as Microsoft, IBM, Amazon, and Google, as well as independent ones, are improving automatic captioning software to make recorded materials accessible to more people.

Currently, real-time captioning is about 90% accurate, although viewers may still see errors in the captions due to misunderstood or misheard words. In some instances, the errors can be due to limitations in the software dictionary.

Voice recognition software provides a faster transcription, and the cost of the service is much cheaper than transcriptions produced by humans.

Human transcription versus voice recognition software  

If you are after quality and accuracy, using a professional human transcriptionist is your best option. The service is more expensive, and the turnaround time may be longer than when you use voice recognition software, but you can expect 99% to 100% accuracy.

Accuracy is vital in the medical, banking, business, and legal sectors, where an erroneous transcription can lead to undesirable results.

  • Human transcriptionists can ignore background noise, which is an issue with most voice recognition software. Humans can filter through the unnecessary noise to deliver an accurate transcription. Automated transcription services cannot handle background noise, which sometimes results in file rejection or inaccurate transcripts.
  • Humans are capable of identifying different speakers. On the other hand, voice recognition software only recognizes the voice but cannot differentiate between speakers, which can be a problem if the recording has several speakers.
  • People have accents and different styles of speaking. Human transcriptionists can easily identify the speakers, whether they are old or young, male or female, fast or slow, soft to hoarse to guttural. They can also understand dialects and accents. These variations in the speech pattern are difficult to program into voice recognition software.
  • Transcribing is not always verbatim. Voice recognition software will automatically transcribe every bit of speech it hears. Humans typically understand the overall context of a speech and can fill in the missing parts. Computers will only transcribe but will not be able to interpret the meaning of certain words or phrases. Voice recognition software usually makes errors with homophones, which can easily lead to mistakes. 

While voice recognition software has come a long way, it still needs human intervention for proofreading and editing.

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