A recursively structured solution for handwriting and speech recognition

This paper extends the basic theory of DAGs (Directed Acyclic Graphs) and their DAG-Compare operation to produce a recursive architecture for language recognition systems. Building upon theory and practical implementation, we treat the cases of multiple interacting levels of language recognition. We propose that DAG data structure and its complementary comparison operation are a structural inductive step for a recursive system architecture. We further propose that a recursive system architecture: 1) divide-and-conquers system design at each level of language recognition and seamlessly integrates different levels of contextual information, 2) allows improvements on core algorithms to have a global and compound system improvement, 3) is amenable for high parallelism and 4) can trade off speed for accuracy. We have implemented a simple prototype cursive word recognition system with two levels of recursive structure and a simple DFT basis. The system integrates a curve matching algorithm, letter recognizer and a full dictionary search and interface to grammar checker. Our cursive word recognizer has good, robust performance (93.6%/98.4%, top 1 and top 2 choices word recognition rate, respectively) which can be further improved with training