This paper proposes a framework to model the dialog interaction process between a developed SDS and the users, as shown in Fig. 2.
The proposed approach aims to model the dialog behavior and detect the miscommunication situations by estimating the probabilities of DS matching and inter-sentential error correction.
This paper proposes a generic dialog modeling framework for a multi-domain dialog system to simultaneously manage goal-oriented and chat dialogs for both information access and entertainment.
Now, developers will have a visual interface for creating skill components, like intents, slots, sample utterances, and the dialog model.
Many existing botnet detection tools were designed based on various assumptions, e.g., the existence of dialog model in BotHunter.
We developed a dialog modeling technique using an example-based approach to implement multiple applications such as car navigation, weather information, TV program guidance, and chatbot.
Hamill describes the development and testing of an automated, hands-free, dialogue-based speech recognition interface for personal emergency response systems PERS prototype with the mounted microphone array, an open-source automatic speech recognition engine, and a 'yes' and 'no' response dialog modeled after an existing call center protocol [71].
One important question in the design of dialog modelling is how to communicate the internal system state of a robot in a way that is understandable to the human user?
So, the key to design the system is the design of human-machine interface (HMI) and the model of human-machine dialog.
With semantic analysis, statistical dialog management models, such as weighted finite-state transducers (WFSTs) [24], Markov decision processes (MDPs) [25, 26], and partially observable MDPs (POMDPs) [8, 13], were proposed for stable dialog flow control, especially in goal-oriented SDSs.
Theoretical modeling can start a dialog concerning other indicators which are potentially useful and shown from previous smaller-scale studies to indicate pain beyond self-reports from the resident, such as the use of nonverbal pain scales.
