Amazon Alexa Team Uses Machine Learning To Better Handle Regional Language Differences
Amazon’s Alexa voice assistant faces a massive challenge: Operating not only as a multi-lingual product, but also ensuring that all regional variants of languages it supports are well understood by Alexa, too.
To help accomplish that, Alexa has been retrained entirely for every variant needed — a time and resource-heavy activity. But a new machine learning-based method for training speech recognition created by Alexa’s AI team could mean a lot less rework in building out models for new variants of existing languages.
In a paper presented to the North American Chapter of the Association for Computational Linguistics, Amazon Alexa AI Senior Applied Science Manager Young-Bum Kim and his colleagues laid out a new system that was able to demonstrate improvements in accuracy of 18%, 43%, 115% and 57%, respectively, on four variants of English (from the U.S., the U.K., India and Canada) used in the trial. READ MORE ON: TECH CRUNCH