1. A method of multi-modal text prediction, comprising: (a) receiving a speech waveform corresponding to text to be recognized; (b) receiving at least one letter corresponding to a portion of the text, the at least one letter being received from an unambiguous data source; (c) dynamically determining a search network based on the at least one letter, the search network including units of sound based on the at least one letter; (d) applying speech recognition techniques that pattern-match the speech waveform against the search network to generate a list of matching text choices; (e) re-ordering the list of matching text choices using a statistical language model, the statistical language model using usage statistics; (f) providing the re-ordered list to a user interface for a determination whether one of the words in the list is the text to be recognized; and (g) reiterating steps (b) to (f) until one of the words in the list is the text to be recognized.
1. A method of multi-modal text prediction, comprising: (a) receiving a speech waveform corresponding to text to be recognized; (b) receiving at least one letter corresponding to a portion of the text, the at least one letter being received from an unambiguous data source; (c) dynamically determining a search network based on the at least one letter, the search network including units of sound based on the at least one letter; (d) applying speech recognition techniques that pattern-match the speech waveform against the search network to generate a list of matching text choices; (e) re-ordering the list of matching text choices using a statistical language model, the statistical language model using usage statistics; (f) providing the re-ordered list to a user interface for a determination whether one of the words in the list is the text to be recognized; and (g) reiterating steps (b) to (f) until one of the words in the list is the text to be recognized. 2. The method recited in claim 1 , wherein the text to be recognized is a single word.