The latest startup I'm working on is Pozotron, an audiobook proofing tool.

We've created software to help people who create audiobooks. Using Pozotron, you can quickly check that an audio recording matches the text of the script.

An example of Pozotron Studio.

You can also follow along, as the cursor moves through the script to highlight each word as it's being read. This lets you click on any word in the script to jump straight there in the audio. (Which is a huge plus to anyone editing a long audio file like this).

Any place that has a missing word, added word, long pause, or other inconsistency is flagged with a red underline that you can review.

The process of recording a new audiobook can be very time consuming. On average it takes 6 to 8 hours of work to create just 1 hour of a finished audiobook. Most of this time isn't spent recording, but going back and editing, proofing, and mastering your original recording.

Using Pozotron, you can quickly check a recording for mistakes in about 1/5th the time it would take you to listen through the whole thing again.

My goal with Pozotron was to bring the latest research in the field of machine learning to the public in a way that is useful today. We have our own machine learning model, on top of a stack that makes it really easy to see and manage the results. I'm really proud of the team who's made it possible, including Ian Roberts, Kostya Glushak, and Ahad Rana.