A novel system for the recognition of spatiotemporal hand gestures used in sign language is presented. While recognition of valid sign sequences is an important task in the overall goal of machine recognition of sign language, recognition of movement epenthesis is an important step towards continuous recognition of natural sign language. We propose a framework for recognizing valid sign segments and identifying movement epenthesis. Experiments show our proposed system performs well when classifying eight different signs and identifying 100 different types of movement epenthesis. A ROC analysis of the systems classifications performance showed an area under the curve measurement of 0.949.