How are these λ values set? Both the simple interpolation and conditional interpolation λ s are learned from a held-out corpus. A held-out corpus is an additional held-out training corpus that we use to set hyperparameters like these λ values, by choosing the λ values that maximize the likelihood of the held-out corpus. That is, we fix the n-gram probabilities and then search for the λ values that-when plugged into Eq. 3.26-give us the highest probability of the held-out set. There are various ways to find this optimal set of λ s. One way is to use the EM algorithm, an iterative learning algorithm that converges on locally optimal λ s (Jelinek and Mercer, 1980) .