9. Apparatus for use in accordance with a dialog system, the apparatus comprising: at least one processor operative to generate at least one language model, the at least one language model being conditioned on a state of dialog associated with the dialog system; and memory, coupled to the at least one processor, for storing the at least one language model for subsequent use in accordance with a speech recognizer associated with the dialog system; wherein the operation of generating the at least one language model conditioned on a state of dialog associated with the dialog system further comprises: (i) dividing training data which is labeled by state into different state sets depending on the state to which the training data belongs; (ii) clustering the state sets into clustered state sets, the clustering comprising combining training data belonging to states that are close to each other based on a distance measure; (iii) building a separate language model for each of the clustered state sets to create a plurality of separate language models; and (iv) building at least one interpolated model by interpolating one or more of the plurality of separate language models with a base model obtained from training data that includes at least some training data used to train all of the plurality of separate language models.
9. Apparatus for use in accordance with a dialog system, the apparatus comprising: at least one processor operative to generate at least one language model, the at least one language model being conditioned on a state of dialog associated with the dialog system; and memory, coupled to the at least one processor, for storing the at least one language model for subsequent use in accordance with a speech recognizer associated with the dialog system; wherein the operation of generating the at least one language model conditioned on a state of dialog associated with the dialog system further comprises: (i) dividing training data which is labeled by state into different state sets depending on the state to which the training data belongs; (ii) clustering the state sets into clustered state sets, the clustering comprising combining training data belonging to states that are close to each other based on a distance measure; (iii) building a separate language model for each of the clustered state sets to create a plurality of separate language models; and (iv) building at least one interpolated model by interpolating one or more of the plurality of separate language models with a base model obtained from training data that includes at least some training data used to train all of the plurality of separate language models. 12. The apparatus of claim 9 , wherein the state corresponds to a prompt that the dialog system presents to a user.