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What AI-based Transcription Cannot do as of Today.


Photo by Markus Winkler from Pexels

For the last 25 years, one of the major concerns of researchers in the field of computer science is to build an Artificial Intelligence (AI) that can accurately recognize and transcript language.

AI-based transcription services have been improved significantly in the past years. Several tech companies have been developing AI transcription tools to bail people out from the tedious chore of penning down a recording word for word. Many professionals are using voice recognition software to convert their video and audio files into the text to execute their work.

Undoubtedly, AI transcription has made translation process more convenient, efficient, customizable, and confidential with the help of a powerful algorithm and high-quality datasets. However, AI transcription is still subjected to limitations despite of these benefits,. In this article, we will be discussing what AI transcription cannot do.

Limitations of AI-based Transcription

Irrespective of the fact that machines are intelligent and can transcribe audio recordings into the readable text; it is yet not capable of comprehending the subtleties of human speech. For instance, background noises, nuances, and technical terms in audio can greatly hinder the accuracy of AI-based transcription.

AI Transcription vs. Manual Transcription

Albeit, AI transcription has come a long way; however, one of its biggest drawbacks is that speech recognition technology only learns after making and correcting a mistake in the text. In other words, speech recognition technology will take some time to understand the nuances found in audio files of human speech.

With regards to that, despite the emergence of AI-powered transcription services, majority of people consider that accuracy of AI transcription is still far from manual transcription services which is about to achieve 99% accuracy. Hence although tedious, manual transcription yields the best results which yet cannot be replaced completely by AI transcription.

AI transcription software also cannot detect multiple speakers and often muddle the specific names of people and places, resulting in inaccurate text. Therefore, manual transcription is used to further polish and rectify the mistakes made by AI transcription software. This implies that despite the advancement in Artificial Intelligence, one needs to manually differentiate the speakers and specific terminology to achieve a flawless transcripted content.  

Experts suggest that human transcriptions override the benefits of AI transcription as the human ear is more attuned to external factors in human speech and therefore cannot misunderstand, omit, or skip words as their automated counterpart (AI transcription) do.

As opposed to AI transcription software, human ears can effectively filter out the background noises in human speech. On the other hand, AI transcription has an error rate of around 12% even when speech recognition software transcripts a clean audio file. Furthermore, humans know the various cultural context and the varying language accents and therefore, are more adept at recognising accents which a machine cannot do.

One of the reasons behind inaccuracy of AI transcription is that AI-powered transcriptions rely on dictionary-based vocabulary, meaning that they are unable to identify different accents, slang or colloquial speech as they can understand only limited words. This makes AI transcription at a substantial disadvantage over human-driven transcription.

A professional transcriptionist can hear audio and video files despite the background noise in it. Human transcriber can accurately interpret words that a machine cannot do as they do understand the individuals, their culture and unique language accent.

As compared to AI technology, manual transcriptionists can better understand speech and accurately interpret regional dialects and foreign accents. Another edge that manual transcription has over machines is that it can distinguish between sound-like words to provide more accurate speech to text transcription.


Photo by Matheus Bertelli from Pexels

Some Other Downsides of AI Transcription

Despite the fact that there are advancements to improve speech recognition technology, it still accompanies with some flaws in AI transcription. These include:

  • inability to differentiate among different speakers, specifically when there is a cross over discussion going on between various speakers.
  • incapable to recognize and spell out specific words and terminologies that are not in English.
  • unable to track words accurately from audio with heavy background noise.
  • incompetent to recognize words when speakers are heavily accented.
  • You might need to spend time on editing the faults in AI transcribed file.

Hybrid Style of Transcription

Companies and business owners that use AI transcription still need to adopt a hybrid model to ensure accuracy in transcription. In a hybrid model, human assistance will be required to achieve 99% accuracy in AI-powered transcription. It is more like proofreading of your transcribed files to remove inaccuracies, typos, and discrepancies which are overlooked by the automated transcription software.  In this model, human transcriber edits the transcript after running it through AI speech recognition software.

The Consideration

All in all, AI transcription software cannot offer 99% accuracy, and therefore, human intervention is still essential. Since both AI transcription and human transcription have both pros and cons, it really depends on how you plan to use the transcript and eventually the time spent on it. Based on the use, you can choose any of the options that best suit your needs and make the most sense. Of note, where time is money, consideration on the budget, the time spent and accuracy of transcription still play a profound role in deciding which transcription to use.

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