The LAST MINUTE corpus comprises records and transcripts of naturalistic problem solving dialogs between N = 130 subjects and a companion system simulated in a Wizard of Oz experiment. Our goal is to detect dialog situations where subjects might break up the dialog with the system which might happen when the subject is unsuccessful. We present a dialog act based representation of the dialog cou...

In this paper, we propose a method of detecting taskincompleted users for a spoken dialog system using an N-grambased dialog history model. We collected a large amount of spoken dialog data accompanied by usability evaluation scores by users in real environments. The database was made by a field test in which naive users used a client-server music retrieval system with a spoken dialog interface...

The structure of a discourse is reflected in many aspects of its linguistic realization, including its lexical, prosodic, syntactic, and semantic nature. Multiparty dialog contains a particular kind of discourse structure, the dialog act (DA). Like other types of structure, the dialog act sequence of a conversation is also reflected in its lexical, prosodic, and syntactic realization. This pape...

Dialog state tracking (DST) is a crucial component in a task-oriented dialog system for conversational information access. A common practice in current dialog systems is to define the dialog state by a set of slot-value pairs. Such representation of dialog states and the slot-filling based DST have been widely employed, but suffer from three drawbacks. (1) The dialog state can contain only a si...

In this paper, we present an approach to spoken dialog management based on the use of a Stochastic Finite-State Transducer estimated from a dialog corpus. The states of the Stochastic Finite-State Transducer represent the dialog states, the input alphabet includes all the possible user utterances, without considering specific values, and the set of system answers constitutes the output alphabet...

This paper describes a new generic architecture for dialog systems enabling communication between a human user and a personal assistant based on speech acts. Dialog systems are often domain-related applications. That is, the system is developed for specific applications and cannot be reused in other domains. A major problem concerns the development of scalable dialog systems capable to be exten...

Cooperative and competitive game dialogs are comparatively examined with respect to temporal, basic text-based, and dialog act characteristics. The condition-specific speaker strategies are amongst others well reflected in distinct dialog act probability distributions, which are discussed in the context of the Gricean Cooperative Principle and of Relevance Theory. Based on the extracted feature...

This paper is the first attempt to learn the policy of an inquiry dialog system (IDS) by using deep reinforcement learning (DRL). Most IDS frameworks represent dialog states and dialog acts with logical formulae. In order to make learning inquiry dialog policies more effective, we introduce a logical formula embedding framework based on a recursive neural network. The results of experiments to ...

Model-based approaches to graphical user interfaces (GUIs) achieved poor acceptance of software engineers because the offer models, architectures, components, frameworks and libraries that restrict the flexibility of development too much. We propose a dialog model which enables flexible development with no restrictions on presentation and application layer and without any implementation-technol...

Natural language understanding and dialog management are two integral components of interactive dialog systems. Previous research has used machine learning techniques to individually optimize these components, with different forms of direct and indirect supervision. We present an approach to integrate the learning of both a dialog strategy using reinforcement learning, and a semantic parser for...