A New Buggy Rule And Template-Template Based Tutorial Dialogue System

We have developed a new buggy-rule and template-template based tutorial dialogue system which is effective not only in simplifying, thus reducing otherwise time-consuming authoring task of template generation but also in improving the system performance. This improved performance is implemented first by the template-template architecture introduced, whereby many different templates can now be integrated into, or equivalently extracted from, a single template-template by applying extraction rules embedded in some of its transitional nodes and secondly by introducing the buggy rules which are capable of identifying and hence generating bugs from learners’ erroneous responses automatically. NLP (natural language processing) technology plays a key role in the system because a parser examines 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 new template-template automaton is expected to play an important role in many other applications including intelligent tutoring systems of both text-based or speech-based dialogue systems, voice-enabling call centre or voice portal systems or in fact any systems focussing o