Dialogue systems are computer systems that communicate with a human in spoken or written form. Their popularity has increased in recent years and they attract a large research and development interest. In this paper, a survey on dialogue systems is presented. A classification scheme is proposed and then the reviewed methodologies are evaluated based on a number of features, in order to obtain a maturity score for each methodology.

A survey on human machine dialogue systems

A method, an apparatus and an article of manufacture for enabling communication between at least two computer applications that is observable to a user. The method includes obtaining a description of functions for each of the at least two computer applications, comparing the description of functions for each of the at least two computer applications, generating a dialog between the at least two applications based on the comparing of the description of functions for each of the at least two computer applications, and making the dialog available to a user.

Intelligent Dialogue Amongst Competitive User Applications

In this paper, we present the development of a tour-guide robot that conducts a poster session through spoken Spanish. The robot is able to navigate around its environment, visually identify informational posters, and explain sections of the posters that users request via pointing gestures. We specify the task by means of dialogue models. A dialogue model defines conversational situations, expectations and robot actions. Dialogue models are integrated into a novel cognitive architecture that allow us to coordinate both human-robot interaction and robot capabilities in a flexible and simple manner. Our robot also incorporates a confidence score on visual outcomes, the history of the conversation and error prevention strategies. Our initial evaluation of the dialogue structure shows the reliability of the overall approach, and the suitability of our dialogue model and architecture to represent complex human-robot interactions, with promising results.

http://turing.iimas.unam.mx/~caleb/pubre/IBERAMIA2010.Aviles2010.Article.pdf

Development of a tour-guide robot using dialogue models and a cognitive architecture

/pdf/virtual-doctor-an-intelligent-human-computer-dialogue-system-st2q9pqbtx.pdf

Virtual Doctor: An Intelligent Human-Computer Dialogue System for Quick Response to People in Need

Advances in developing dialogue systems regarding speech recognition, language understanding, and speech synthesis. Dialogue systems to support human interaction with a robot efficiently by using spoken language. Facilities that provide convenience in carrying out daily activities for someone, such as older people, are necessary. The existence of Human-Robot Interaction (HRI), so that this interaction can give orders to the robot to do work that cannot be done by humans. This study presents a dialogue management system for HRI with a comparison sentence similarity method between TF-IDF (Term Frequency-Inverse Document Frequency) Cosine Similarity Algorithm and Jaccard Coefficient and using Finite State Machine (FSM). Dialogue Management is a way to find the response of the answer. When the user says something or in other words, is responsible for managing the flow of the conversation to command the robot. TF-IDF is used to give the weight of the term relationship and comparison between Cosine Similarity and Jaccard Coefficient for comparison method to determine the classification of similarity sentences from the dialogue manager to improve the intent of the dialogue, for the FSM method to set the sequence flow dialogue. We use Google Cloud Speech API as an engine for speech to text using Kinect V2 as an audio sensor. There are eight scenarios created in this system. The speech recognition process using Google Speech for an average of 2.62 seconds shows a reasonably fast response. TF-IDF Cosine Similarity method can produce enough accuracy of 97.43%, and Jaccard Coefficient indicates an accuracy level of 91.57%. The state of the FSM method can be considered as an efficient structure for building dialogue management.

Human-Robot Interaction Based on Dialog Management Using Sentence Similarity Comparison Method

This paper presents a dialogue system for intelligent service robot application. The dialogue system consists of an audio speech recognition module, a text-to-speech conversion module, and a dialogue manager for supervision of timely conversion of input command to output robotic service. The dialogue manager is implemented in the framework of task supervisor for HRI(Human-Robot-Interface) module and makes use of finite state machine module for each robotic service. Since the number of services generated grows larger as the complexity of robotic task increases, the set of finite state machine modules is designed in compact modular form in the dialogue manager enhancing the capability of intelligent service robot handling various missions. The effectiveness of proposed dialogue system is demonstrated by applying it to information delivery service of weather and news, scheduling service, and entertainment game service for robotic user.

Implementation of dialogue system for intelligent service robots

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Implementation of dialogue system for intelligent service robots