Most people who try automated transcription services are disappointed by the “accuracy.” 

But the single biggest factor in transcription accuracy isn’t the transcription itself – most services can accurately transcribe clean audio at 95%+. 

So what matters more than raw transcription accuracy?

Speaker splitting 
the ability of the service to accurately understand who is speaking when

Most services use open-source software to “guess” who is speaking by analyzing differences in pitch and tone. Sounds cool, right? Unfortunately it doesn’t work. Typical problems include:

  • their systems can’t tell the difference between similar sounding speakers
  • they often “guess” more speakers are on the call than actually are
  • they aren’t able do speaker-level analysis to understand if one caller was angry or excited – this can only be done at the conversation-level

Fortunately, there is a better way. We’ll share in a future post how Jog developed an entirely new approach to deliver, for the first time, 100% accurate speaker-splitting. 

For now, take it from customers – Jog is the most accurate transcription platform available:

Categories: Call Transcription

Sam Gaddis

Making sense of voice data. Founder of Jog.ai

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