There are a million and one services for voice transcription on the market. But even with just one job to do, I’ve never seen a service that can handle the long tail of vocabulary used in the real world. This is particularly challenging if you’re a startup trying to sell your service to enterprises that rely on accurate transcription for their operations.
Jon Goldsmith, co-founder of Tetra, a voice transcription startup, understands this challenge — in fact, he is even willing to admit that he hasn’t 100 percent cracked the problem. But Goldsmith believes the answer lies in deep learning, and he’s setting out to prove it with a $1.5 million seed round led by Amplify Partners, with participation from Y Combinator and a number of angels.
I dropped by the Tetra office to check out what Goldsmith, his co-founder Nik Liolios and one other engineer had created. Goldsmith gave me a call using his smartphone with the Tetra app installed. As he and the deep learning models running in the background listened, I threw out a barrage of challenges for the transcription service.
Speaking at varying speeds, throwing out numbers, startup names and other tough words did stump Tetra to some degree — but to be fair, there is no AI that I haven’t broken. Given how easy Tetra is to use, I could see…