The seed round was co-led by Merus Capital and GoHub Ventures with backing from APX and Techstars.
"training latest deep learning models accurately on very small data sets, which any local, low-resource language usually suffers from, is a very challenging task because models are usually designed to perform well in English with terabytes of available text and speech data but not in languages with a few hundred megabytes of data."
The seed round was led by Merus Capital with participation from APX, Techstars, Verissimo, and angel investors.
"training latest deep learning models accurately on very small data sets, which any local, low-resource language usually suffers from, is a very challenging task because models are usually designed to perform well in English with terabytes of available text and speech data but not in languages with a few hundred megabytes of data."
