A dialogue tutoring system exploiting extracting-rule-embedded-template structure and the expanding powers of buggy rules

This paper develops a new tutorial dialogue system exploiting the extracting-rule-based extracting-rule-embedded-template structure and the expanding powers of buggy rules. The system is effective not only in simplifying, thus reducing otherwise time-consuming authoring task of template generation but also in improving the system performance. The extracting-rule-embedded-template architecture introduced leads to system simplification and performance improvement firstly because it allows many different templates to be integrated into, or equivalently to be extracted from, a single extracting-rule-embedded-template by applying extracting rules assigned to some of its transitional nodes and secondly because the buggy rules introduced are capable of identifying and hence generating bugs from learners´ erroneous responses automatically. The NLP (natural language processing) technology plays a key role in the system development because a parser is used to examine the syntactical structure of the learner´s free format response while its semantic structure is examined by matching the respective response to the semantically equivalent paths of template databases prepared. The extracting rule-based and buggy rule-based extracting-rule-embedded-template structure is expected to play an important role in many applications including both written and spoken tutoring systems, voice-enabling call center or voice portal systems or in fact any system focusing more enhanced human computer interfaces, implementing more natural human computer interactions between the system and humans.