1. A method, comprising: receiving with a computing device digital data representing a string of images, the images representing at least part of a user; processing the data using software to detect therefrom a string of gestures of the user, each gesture represented as a vector; mapping the vectors to a string of phonetic elements; and identifying one or more words in a written language, the one or more words corresponding to the string of the phonetic elements; wherein the written language is a one of a plurality of regional languages, mapping the vectors to the string of phonetic elements comprises selecting each phonetic element in the string of phonetic elements in a manner that is agnostic to any one of the plurality of regional languages, and identifying the one or more words comprises selecting a contextual dictionary specific to a selected one of the plurality of regional languages, the selected one corresponding to the written language, and translating the string of phonetic elements to the selected language; and wherein further each vector comprises a position in n-degree space, and wherein mapping further comprises translating the position in n-degree space to a position in m-degree space, where n>m, and selecting a phonetic element uniquely associated with the position in m-degree space, translating includes accessing a dictionary to map positions in n-degree space to corresponding positions in m-degree space, and the method further comprises using principal components analysis to adaptively learn the dictionary.