A segmentation procedure for connected word recognition based on estimation principles

Recognition of connected word strings can be performed by segmenting the word string automatically into single-word components which are then classified by a single-word recognition system. We propose and investigate a segmentation procedure which is based completely on statistical principles. An estimation algorithm, adapted to the statistical data of the signal parameters, determines the word boundaries. This procedure, which offers several advantages over other methods, has been tested with connected digits. The results show that an estimation algorithm based on quadratic polynomials yields sufficiently accurate segmentation. Recognition results for 2-to 4-digit strings are presented in this paper.