Dot Translate is the first braille translator based on AI. It can translate any digital text to braille on its own, at near-human accuracy. Because it’s being trained with millions of most accurate human translation samples / data to understand context.

Dot Translate is accessible through an intuitive web interface, Dot devices and other digital braille devices. It can translate a wide range of formats and sources: type, e-pub, pdf, txt, doc, rtf, html and even voice. Through the bookmark feature, users can directly translate and format whole websites. Dot Translate can be integrated by third party services and products. But most importantly: While existing braille translation software costs up to $700, Dot Translate is free to use. This is important, because due to the nature of Machine Learning and a feedback tool, usage increases the accuracy.

Dot Translate is the first braille translator based on AI. It can translate any digital text to braille on its own, at near-human accuracy. Because it’s being trained with millions of most accurate human translations.

Braille translation is highly complex: Grade 2 Braille – the standard for longer text – relies heavily on contractions. This leads to ambiguity, where meaning depends on context and up to five consecutive rules for a single letter. So far, even the best existing software requires additional input by human experts. Existing braille translation software works by applying a small set of pre-defined rules, which doesn’t cover many cases.

Dot Translate enhances rule-based translation with AI: Grade 2 Braille translation comes down to understanding the context of the word and finding the shortest accurate contraction.

For accuracy, Dot Translate relies on a character-based word model based on a sequence to sequence neural network, trained with millions of character sequences from most accurate human translations. Then a beam search algorithm looks at the most promising candidates from the first step and determines the shortest accurate translation. Together, these two methods result in the shortest, most accurate translation in the specific context.