Vlingo’s system starts with a basic statistical language model to make the best guess about what you say. It then improves upon that by taking into account context, and positive and negative user feedback down to the individual. Context helps the system by narrowing the number of possible words you said. For instance, if the context is an address, the number of possible street names is limited to the ones in the city. User feedback correcting the system’s output or leaving it be helps the system learn how you speak (e.g correcting Austin to Boston).
