We continue our investigations of Word-Phrase-Entity (WPE) Language Models that unify words, phrases and classes, such as named entities, into a single probabilistic framework for the purpose of language modeling. In the present study we show how WPE LMs can be adapted to work in a personalized scenario where class definitions change from user to user or even from utterance to utterance. Compared to traditional classbased LMs in various conditions, WPE LMs exhibited comparable or better modeling potential without requiring pre-tagged training material. We also significantly scaled the experimental setup by widening the target domain, amplifying the amount of training material and increasing the number of classes.

Two O(N log N) heuristic approaches for planning viewpoints in 2D known environments are described. Both are based on the generalized Delaunay triangulation of a polygon with holes. The main difference between them is the heuristic strategies used to merge the triangles to form the partitioning or covering star polygons. When the environment needs to be explored, an O(N/sup 2/ log N) heuristic scheme which successively selects the viewpoints and views for mobile robots is used. Upper bounds on the number of planned viewpoints and views for each scheme are estimated.>