Abstract
Sign language has an interesting characteristic that a change in part of the manual motion properties in hand-shape, location, movement often results in changing the meaning of signs. It is particularly called a minimal pair that the difference of properties between two signs is only one feature element. In building an electronic sign dictionary system, a couple of signs with similar manual motion properties play an important role in the retrieval, registration and synthesizing mechanism. This paper proposes a method for extracting a couple of signs with similar manual motion properties from a given set of signs. The method is based on the similarity between two signs, which is derived from the longest common subsequence (LCS) between manual motion descriptions (MMDs). It can be considered that a MMD represents information extracted from a series of motions of a sign. By computing the feature vectors of n properties from MMDs and plotting them in the n-dimensional Euclidean space, an angle between two vectors can be considered as the similarity between two signs. However, when the feature vector can be considered as a string of MMD, the similarity can be obtained by string matching between the two MMDs. The results of evaluation experiments show the applicability of the proposed method.
