Conceptual language model design for spoken language understanding

This paper describes the construction and use of language models specific to semantic concepts. A tolerance mechanism is introduced in order to design conceptual constituents that cover longer word patterns while remaining robust to spontaneous speech disfluencies and recognition errors. These models are obtained from sentence patterns which grow from essential information to longer sequences of words. It is shown that these augmented conceptual constituents provide reductions in concept error rates on a spoken dialog application task. The composition of semantic constituents into semantic structures is discussed together with the introduction of language models for semantic composition. Experiments are described which show the advantage of using these language models to take into account structured semantic information.