Spoken language interfaces based on interactive semantic language
models allow probabilities for
hypothesized words to be conditioned on the semantic interpretation of
these words in the context of some interfaced application environment.

This conditioning may allow users to avoid recognition errors in an
intuitive way, by adding extra, possibly redundant description.

This paper evaluates the effect on error reduction of redundant
descriptions in an interactive semantic language model.

In order to evaluate the effect in natural use, the model is run on
rich domains, supporting references to sets of individuals (instead of
just individuals themselves) arranged in multiple continuous
dimensions (a 2-D floorplan scene).

Results of these experiments suggest that an interactive semantic language
model allows users to achieve significantly higher recognition accuracy by 
providing additional redundant spoken description.