Dialog-context dependent language modeling combining n-grams and stochastic context-free grammars

In this paper, we present our research on dialog dependent language modeling. In accordance with a speech (or sentence) production model in a discourse we split language modeling into two components; namely, dialog dependent concept modeling and syntactic modeling. The concept model is conditioned on the last question prompted by the dialog system and it is structured using n-grams. The syntactic model , which consists of a collection of stochastic context-free grammars one for each concept, describes word sequences that may be used to express the concepts. The resulting LM is evaluated by rescoringN-best lists. We report significant perplexity improvement with moderate word error rate drop within the context of CU Communicator System; a dialog system for making travel plans by accessing information about flights, hotels and car rentals.