Systems and methods for adaptive handwriting recognition

A method for building a handwriting recognition system, comprising:

• building at least one generic classifier utilizing handwriting data associated with a plurality of users;
• building at least one user specific classifier utilizing handwriting data supplied by at least one selected from the group comprising a specific user and both a specific user and a plurality of users, wherein at least one tying class having at least one tying set comprising a plurality of characters exhibiting similar features associated with the specific user is employed to train the at least one user-specific classifier, the features of a character within the tying set can be extrapolated to the other characters in the tying set without requiring the specific user to enter all characters of that particular tying set;
• and
• employing the at least one generic classifier and the at least one user-specific classifier in connection with the classification of handwriting data.

A system for recognizing handwriting, comprising:

• means for generically determining a classification of handwriting information trained via data from multiple users;
• and
• means for specifically determining a classification of handwriting information trained, at least in part, via data from a specific user;
• and
• means for operably utilizing both the generically determining means and the specifically determining means to classify handwriting data, wherein at least one tying class having at least one tying set is employed to train the specifically determining means, the features of a character within the tying set can be extrapolated to the other characters in the tying set.