From robust spoken language understanding to knowledge acquisition and management

摘要

The recent evolution of Carl, an intelligent mobile robot, is presented. The paper focuses on robust spoken language understanding (SLU) and on knowledge representation and reasoning (KRR). Robustness in SLU is achieved through the combination of deep and shallow parsing, tolerating non-grammatical utterances. The KRR module supports the integration of information coming from different interlocutors and is capable of handling contradictory facts. The knowledge representation language is based on semantic networks. Question answering is based on deductive as well as inductive inference. A preliminary evaluation of the efficiency of the SLU/KRR system, for the purpose of knowledge acquisition, is presented.