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How To Get The Best Results From AI Transcription

The use of transcripts has expanded beyond records of speeches sent to media outlets and legal court proceedings. They are now also widely used as records for lectures, virtual conference calls, and meetings hence there was a need for a quicker and more efficient transcription process as the demand for it is getting bigger and bigger. This was a gap filled in by Artificial Intelligence (AI) technologies.

In this day and age, AI is now used to make the transcription process quicker and more efficient. These process used to take days for a single human to transcribe before will only take a few hours today. In some cases, it can even take a matter of a few minutes to transcribe.

It is important to know the factors affecting the quality of the transcription and how to make the best out of it If you are planning to use AI transcription any time soon.

Factors that Affect the Results from AI Transcription

AI transcription is still far from being perfect, so it is vital to know the different factors affecting the quality of the transcript you get from AI-based transcription.

Background Noise

Firstly, background noise can significantly affect the accuracy of the AI-based transcription service. This is because AI is trained with algorithms to recognize and interpret particular sound frequency. When these sounds are disrupted by background noise, there is a high chance of being misinterpreted by the AI.

This factor is also something that significantly affects even seasoned transcriptionists. Although they have years of training, the human ears can misinterpret sound when the background noise distorts it.

The Speaker’s Pronunciation

The speaker’s pronunciation of words can also affect AI transcription accuracy for the same reason as the background noise. If the speaker in your audio file is a non-native English speaker, the AI transcription might have a harder time transcribing your file accurately than when the speaker is fluent in English.

Aside from the pronunciation, if the speaker talks in a shouted or overly dramatic way, it will also affect the transcription accuracy. The reason for this is also the same as what is mentioned above.

Number of Speakers in a Recording

Another huge factor that affects the accuracy of AI transcription is the number of speakers in a recording. This makes it challenging for the algorithm to detect when there are cross-talking within speakers; hence it can create a lower accuracy in the final outcome. The algorithm cannot properly translate the speakers’ overlapping speech.

Use of Jargons

If the file you want to transcribe contains jargon from specific fields, it may not be transcribed correctly by the AI. Most AI-base transcription engines are trained with general voice data which is only capable of transcribing common usage of the English language.

Tips on How to Get the Best Result From AI Transcription

Now that you know the different factors that affect the AI transcriptions, here are some tips that will help you get the best possible result.

Ensure the Audio Quality is Good

As you already know, audio distortion, audible background noise and music affect the AI-based transcription quality. Thus, it is essential to ensure that the file you put into the AI transcription service is of the best quality.

There are several ways to optimize the audio quality for AI transcription. One way is to pay close attention to room acoustic when recording. Remember, big and empty rooms can create echoes and lessen the sound quality. Meanwhile, a room with loud background chatter or noise can also do the same thing.

It is also good to use high-quality equipment and ensure that they are strategically located in a room. The equipment must amplify the speaker’s voice allowing it to be louder and more precise.

As for the strategic equipment location, it will enable the efficient capture of the speaker’s voice. Some of the best spots for equipment, such as a microphone, is to put it close to the speaker’s mouth.

Using an audio sound editor and saving the file in M4A format is also advisable. These can help improve the audio quality of the file. If you cannot save it in M4A format, WAV or MP3 are also good choices.

Have Fewer Speakers at a Time

Overlapping conversation makes it difficult for AI to transcribe in text properly, which is why it is a good idea to remind your speakers to avoid speaking over each other. Having a slight pause before the next speaker will be advisable. It ensures the clarity of the speaker’s voice and the accuracy of the transcription.

If you are transcribing court proceedings, speeches, or lectures, overlapping conversations is not really a big deal because it does not happen often. However, this tip tends to be more appropriate when you are transcribing debates or podcasts.

Custmisation of AI software

If there is terminology needed for a specific industry, you can always have a customised AI transcription service for your usage. This could be done with a set of data with specific jargons, the engine will be trained using that. On top of this, this service could be kept onsite if you have a server or on the cloud. This service will be solely for your use.

In Short,

The information above sums up what is AI transcription and how you can make the best out of it. Indeed, AI transcription is very helpful, especially when you need to transcribe files quickly. However, it is not perfect. It may require you to put in some extra effort to ensure the best results.

If you are looking for an AI transcription service that is easy to use, accurate and quick, then you should check out Senseofwonder.ai. Their trusty AI allows you to transcribe your audio files in 3 quick steps.

Senseofwonder.ai also has the latest Automated Speech Recognition software for reliable transcription and customization features, making them even more perfect for all your needs. Visit their website today, and get the right AI transcription solution for your needs!

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.