On the use of time compression for word-based recognition

Dynamic time warping is a very efficient technique in dealing with the problem of time distorsion between different pronunciations of any given worm. However when, in a word-based recognition system(isolated or connected words), time normalisation is solely based on a DR-matching process, much processing time is necessitated. Another characteristic is that the general constraints used to optimise the DP-matching algorithm impose a severe limit on acceptable time distorsions. In this paper, we evaluate the interesting aspects of non-linear time compression methods which carry out a first time normalisation prior to DP-matching in word-based recognition. We describe three non-linear compression techniques, which have come under consideration during the study of recognition systems developed at LIMSI. These non-linear compression methods are compared to linear compressions in an isolated word recognition framework for different vocabularies.