Transcribe audio to text automatically

Don’t be manual!

To transcribe audio to text automatically you don’t have to be a software or web developer or even know how to code in order to automate some of the more mundane tasks on your list of things to do on the internet. There are services available that make you feel like you have an assistant who does your work automatically, with minimal instruction.

Good leaders do things ‘automatically’ – make decisions, communicate effectively, challenge and motivate people, be accountable, and measure and reward performance. And mothers certainly do things ‘automatically’ – feed their children, cry when their children cry, sacrifice sleep and free time, and clean all day!

We are used to the ease of things happening ‘automatically’ which make our days easier – booms and garages going up, planes descending and landing, doors opening before we even get close enough to touch them, escalators carrying us along with our legs not needing to move, and sensor lights that have a way of knowing exactly where we are!

Washing machines and driers have replaced scrubbing by hand and sunlight as their automation is ‘automatically’ faster. And very few people cook over a fire out of necessity, as a button on the oven heats to scorching temperatures in a matter of minutes.

Transcribe audio to text automatically – the options?

But how do we transcribe audio to text automatically? Well, there are essentially three options for this.

First, you could use software designed to transcribe audio to text automatically.

Second, you could employ a human trained to transcribe audio to text.

And third, you could use a hybrid model – a combination of software and humans – for the churning out of transcription in the best way possible: fast and accurate!

Best automatic transcription option?

The problem with software to transcribe audio to text automatically is that, even after years of study and development, accuracy is low because language is complex. The more speakers in a file, the heaviness of accents, the rapidity at which people speak, the technicality of subject matter, all serve to confound the software.

Human transcription is much more accurate, but lacks the speed of software, which produces transcripts at near to real-time.

So the hybrid model for transcribing audio to text automatically may be just the answer you need. Basically, the software transcribes quickly and people “check” the transcripts to fix the inaccuracies.