Abstract: A system for analyzing language using supervised learning method. The system extracts portions matching with structures of problem expressions from a raw corpus that is not supplemented with analysis information, then converts the extracted portions corresponding to the problem expressions into supervised data including problems and solutions and stores in the data storage. The system extracts sets of solutions and features from the supervised data stored in the data storage, carries out machine learning processing using the sets and stores learned results as to what kind of solution is the most straightforward for which feature in the learning results database. The system then extracts sets of features from the inputted object data, extrapolates analysis information showing the most optimum for a certain feature, from the sets of features based on the learning results database.

Abstract: An object of the present invention is to provide a method of segmenting hand gestures which automatically segments hand gestures to be detected into words or apprehensible units structured by a plurality of words when recognizing the hand gestures without the user's presentation where to segment. Transition feature data in which a feature of a transition gesture being not observed during a gesture representing a word but is described when transiting from a gesture to another is previously stored. Thereafter, a motion of image corresponding to the part of body in which the transition gesture is observed is detected (step S106), the detected motion of image is compared with the transition feature data (step S107), and a time position where the transition gesture is observed is determined so as to segment the hand gestures (step S108).