7 Fatal Flaws of AI Transcriptions You Should Know

By 2030, the artificial intelligence (AI) market will reach $1.85 trillion.

(Next Move Strategy Consulting)

No matter what industry you work in, one thing is certain: AI has (or will have) a big part in it.

We Forum estimates that by 2025, about 97 million people will be needed to fill AI-related roles.

Indeed, AI tools bring significant benefits to our daily work. One of the most common tools is AI audio transcriptions (also known as automated transcriptions, speech-to-text transcriptions, or machine transcriptions) that transcribe audio into text files to help researchers, business managers, and other professionals streamline their workflow and improve team collaboration, among other advantages.

AI transcriptions have become more popular than human transcriptions due to their speed and ease of use. However, AI transcriptions are very limited.

If you’re considering making the switch from human transcriptionists to AI transcription services, here are seven fatal flaws of AI transcriptions you should know first:

7 Crucial Disadvantages Of AI Transcriptions

Always Produces Inaccuracies

Despite how much AI transcriptions have advanced, you’re never guaranteed a 100% accuracy rate. The technology is too limited to understand human speech from a video or audio file completely.

Their speed may compensate for this limitation. On the contrary, you may spend additional time correcting the automated transcript for grammar or vocabulary errors. At worst, you’ll need to return to the original audio recording to understand the dialogue the AI tool tried to transcribe.

Struggles With Complex Audio

Generally, automated transcription software has a hard time dealing with complex audio that includes:

• Cross-talk - Multiple speakers talking over each other causes problems in speaker identification and overall speech recognition
• Background noise - Sounds in the background of the recording can skew the AI’s processing of the dialogue
• Accents and dialects - Unique pronunciations and inflections can throw off most AI tools

More often than not, many audio files contain at least one of the transcription challenges above. While human transcriptionists can sift through the noise, AI transcription tools will struggle with it.

Falls Apart Due To Poor Audio Quality

AI tools work best with crystal-clear audio recordings. If your audio is muddled, the automated transcript will be highly inaccurate. There are several ways to improve your audio quality for more accurate AI transcripts, but all of those methods come at the cost of your convenience. The transcription software should adjust to your needs, not vice versa.

Finds It Challenging To Tell People Apart

Speech recognition software has evolved to the point where it can differentiate two or more speakers in an audio or video file. Unfortunately, speaker identification remains a barrier for AI tools. 

Imagine your audio recordings have any one of the following:

• Two or more speakers having similar or identical voices
• Several speakers that are either all-male or all-female
• Speakers that talk in varying degrees of volume or tone

Automated transcription software shines with audibly distinct speech. However, audio recordings with clear speech are rare in reality.

Lacks The Ability Of Capturing The Full Context

If you want pure verbatim transcriptions, you may want to pass up on automated transcription software.

Pure verbatim transcriptions offer the advantage of giving you the full context of an audio recording. Depending on your needs, filler words, stutters, and other factors may be helpful.

Because most speech recognition software is designed only to recognize words, non-verbal cues and other “filler audio” are omitted. On the bright side, AI can produce smart verbatim transcriptions at best. However, this means you’re always missing out on the full context of the dialogue.

Difficulties With Jargon

Industry-specific jargon and acronyms are among the most challenging obstacles to AI transcription. Most software is trained with conversational vocabulary. In the face of highly technical terminologies, their speech recognition capabilities will waver.

The Horrors Of Homonyms and Homophones

Homonyms and homophones are nuances in language that significantly challenge automated transcription tools.

Homonyms are words that are spelled the same but have different meanings and/or pronunciations, while homophones are words that sound identical.

AI transcription software only interprets dialogue at face value. Without contextual understanding, it’s unable to discern nuances, leading to inaccuracies in the transcripts.

AI Or Human Transcription?

Despite its flaws, automated transcription software may still appeal to you due to its quickness and convenience — so much so that you may be willing to put up with inaccurate AI transcripts as long as they’re usable.

Ultimately, whether an AI transcriber or human transcriptionist is the best for your needs is up to you.

• AI transcription can rapidly produce transcripts of your audio recordings with default formatting that is usually passable.
• Human transcription can create highly accurate transcripts that are either pure verbatim, smart verbatim, or non-verbatim, have clear speaker identification, and can match your formatting specifications.

Human Transcriptionists Are Still The Way To Go

Human transcriptionists are still your best choice if you're pursuing quality transcripts. Should speed be one of your top priorities, human transcription services like TranscriptionWing can offer rush transcription services that deliver transcripts in as short as 4 hours or by the next business day in addition to quality, flexibility, and customer service.

In other words, human transcriptionists offer something that AI transcriptions can never have: the human touch.

Witness the true potential of human transcriptionists in delivering transcripts that meet all your needs with TranscriptionWing!