As stated earlier, the role of noisy visual input in our model is as the likelihood term in a Bayesian inference about sentence form and identity.
if we denote the input obtained thus far from a sentence as I, all the information pertinent to the reader's inferences can be encapsulated in the form p(I|w) for possible sentences w. We assume that the inputs deriving from each character position are conditionally independent given sentence identity, so that if w j denotes letter j of the sentence and I( j) denotes the component of visual input associated with that letter, then we can decompose p(I|w) as ∏ j p(I( j)|w j ).