Emergent computational dialogue management architecture for task-oriented spoken dialogue systems

This paper proposes a new dialogue management architecture for human-machine speech communication systems. In our daily speech communication, incremental, non-deterministic and quick-response behaviors are required for effortless information interchange. Emergent computational architectures, proposed in the robot control domain, are promising to enable such features. The dialogue manager (ECL-DIALOG) consists of multiple “phrase pattern” detectors as input sensors. The CFG driven phrase detectors search for phrase patterns in user utterances and generates numerous emergent slot-filling signals. The system integrates them according to their “phrase pattern” priorities and updates the current taskcompletion context. When a slot value is updated, the system generates an appropriate response. For example, when the system finds a new slot value from user utterances, the system generates a chiming utterance “yeah”. When the context slot is replaced by a different EMERGENT COMPUTATIONAL DIALOGUE MANAGEMENT ARCHITECTURE FOR TASK-ORIENTED SPOKEN DIALOGUE SYSTEMS