AI, AI, AI. The tech race has centered on using AI, or artificial intelligence, to improve productivity and streamline business practices. In reality, we use AI in our personal lives every day. We don’t call it AI. We call it Siri or Alexa. It plays our music, helps us shop, and gives us directions. We love it and it works, most of the time. When it doesn’t work, news stories and comedy routines abound with AI as the butt of the joke.
Now, transfer that funny AI blooper into the quarterly sales report. Let’s say, AI gives you 90 to 100 instead of 9,200 for your sales. Suddenly no one is laughing. AI transcription can be fast and cost effective initially, but it comes with a price. Even with all the technological advances, human transcription offers many advantages over AI.
What is AI?
Before we compare AI to human transcribers, we need to ask, what is artificial intelligence, especially as it relates to transcription? Essentially, it’s a series of computer algorithms that analyze input data. Period. So where does the intelligence come in? Simply put, AI uses the final output and re-analyzes it to “learn.” In the case of speech recognition, which we use for transcription, the input data are sounds. Words are broken down into phonetic sounds, analyzed by the algorithms and translated into written characters. For example, do you say caramel with two syllables (car-mel) or with three (care-uh-mel)? Since speech recognition analyzes only sounds, it sees this as two different words. Thus, both pronunciations need to be included in the algorithmic analysis or you get bad output. A human transcriber will always outperform AI because the human brain has more to rely on than just these algorithms.
AI Fails with Non-English Speakers
First, a human transcriber has a much easier time with ESL (English as a second language) speakers or speakers with accents. Scientific American published an article in July 2020 highlighting the bias speech recognition software has toward white American pronunciation (https://www.scientificamerican.com/article/speech-recognition-tech-is-yet-another-example-of-bias/ ). Like it or not, the output quality for AI is directly dependent on accent, dialect, and speech pattern.
AI Fails with Background Noise
AI also has trouble picking up speech in noisy environments and distinguishing background or extraneous noises. Speech recognition output can filter out loud noises based on the decibels, but background conversations or comments muddle the SR output.
AI Fails in Multi-Speaker Settings
TruTranscripts transcribers can identify multiple speakers and correctly attribute speech to each individual. This has become much more important in the past year with the increased use of online meetings. Of course, AI particularly falls flat when people are speaking over each other. The output becomes a mixed-up jumble of just seemingly random words. Our transcribers distinguish individual speakers and produce a transcript of the conversation with each speaker’s words on a separate line, even when everyone is shouting out ideas during a brainstorming session.
AI Fails in Critical Thinking
Finally, the most important thing a human transcriber offers is critical thinking as it relates to the content itself. AI just can’t do it. It’s not designed to pick up on subtle cultural references or corporate jargon. It can’t fact check name and place spellings. We can. AI can’t make a notation to fact check these things for you either. Will you remember? TruTranscripts transcribers make a note in the transcript if we cannot verify a name or place as a subtle reminder for you. That’s what we call the human touch.
Really, what it boils down to is, AI may be able to replace the human fingers on the keyboard, but it’s the human ear and the human brain that makes TruTranscripts transcription quality so much better. Don’t settle for less than your business deserves. Contact us for more information or click here for a free quote.