Mixed-initiative Personal Assistants

Specification and implementation of flexible human-computer dialogs is challenging because of the complexity involved in rendering the dialog responsive to a vast number of varied paths through which users might desire to complete the dialog. To address this problem, we developed a toolkit for modeling and implementing task-based, mixed-initiative dialogs based on metaphors from lambda calculus. Our toolkit can automatically operationalize a dialog that involves multiple prompts and/or sub-dialogs, given a high-level dialog specification of it. Our current research entails incorporating the use of natural language to make the flexibility in communicating user utterances commensurate with that in dialog completion paths

CSE: U: Mixed-initiative Personal Assistant Agents

Specification and implementation of flexible human-computer dialogs is challenging because of the complexity involved in rendering the dialog responsive to a vast number of varied paths through which users might desire to complete the dialog. To address this problem, we developed a toolkit for modeling and implementing task-based, mixed-initiative dialogs based on metaphors from lambda calculus. Our toolkit can automatically operationalize a dialog that involves multiple prompts and/or sub-dialogs, given a high-level dialog specification of it. The use of natural language with the resulting dialogs makes the flexibility in communicating user utterances commensurate with that in dialog completion paths—an aspect missing from commercial assistants like Siri. Our results demonstrate that the dialogs authored with our toolkit support the end user’s completion of a human-computer dialog in a manner that is most natural to them—in a mixed-initiative fashion—that resembles human-human interaction

Robotics for social welfare

Supported by developments in the field of social robotics, virtual worlds and ICT tools it is possible to build new solutions in health and welfare. Two projects are described in this article. They are intended to improve efficiency and quality of current therapeutic procedures. The ESTIMULO project improves emotional and cognitive status of people with dementia using a reactive pet-robot. The ELDERTOY project modifies the classical concept from the toy industry to develop a new solution for the aged people. ELDERTOY involves a double purpose, fun and therapeutic. In a complementary way, these projects aim to be an example of the breaking of the technology gap both of seniors and of people with disabilities. Therefore, the ultimate goal is to promote and adapt scientific and technological knowledge to be applied to improve significantly the standard of quality of life in society

Natural Language, Mixed-Initiative Personal Assistant Agents

The increasing popularity and use of personal voice assistant technologies, such as Siri and Google Now, is driving and expanding progress toward the long-term and lofty goal of using artificial intelligence to build human-computer dialog systems capable of understanding natural language. While dialog-based systems such as Siri support utterances communicated through natural language, they are limited in the flexibility they afford to the user in interacting with the system and, thus, support primarily action-requesting and information-seeking tasks. Mixed-initiative interaction, on the other hand, is a flexible interaction technique where the user and the system act as equal participants in an activity, and is often exhibited in human-human conversations. In this paper, we study user support for mixed-initiative interaction with dialog-based systems through natural language using a bag-of-words model and k-nearest-neighbor classifier. We study this problem in the context of a toolkit we developed for automated, mixed-initiative dialog system construction, involving a dialog authoring notation and management engine based on lambda calculus, for specifying and implementing task-based, mixed-initiative dialogs. We use ordering at Subway through natural language, human-computer dialogs as a case study. Our results demonstrate that the dialogs authored with our toolkit support the end user\u27s completion of a natural language, human-computer dialog in a mixed-initiative fashion. The use of natural language in the resulting mixed-initiative dialogs afford the user the ability to experience multiple self-directed paths through the dialog and makes the flexibility in communicating user utterances commensurate with that in dialog completion paths---an aspect missing from commercial assistants like Siri

Automatic sentence stress feedback for non-native English learners

1121Ysciescopu

Mining Mixed-Initiative Dialogs

Human-computer dialogs are an important vehicle through which to produce a rich and compelling form of human-computer interaction. We view the specification of a human-computer dialog as a set of sequences of progressive interactions between a user and a computer system, and mine partially ordered sets, which correspond to mixing dialog initiative, embedded in these sets of sequences—a process we refer to as dialog mining—because partially ordered sets can be advantageously exploited to reduce the control complexity of a dialog implementation. Our mining losslessly compresses the specification of a dialog. We describe our mining algorithm and report the results of a simulation-oriented evaluation. Our algorithm is sound, and our results indicate that it can compress nearly all dialog specifications, and some to a high degree. This work is part of broader research on the specification and implementation of mixed-initiative dialogs

A Language-Based Model for Specifying and Staging Mixed-Initiative Dialogs

Specifying and implementing flexible human-computer dialogs, such as those used in kiosks, is complex because of the numerous and varied directions in which each user might steer a dialog. The objective of this research is to improve dialog specification and implementation. To do so we developed a model for specifying and staging mixed-initiative dialogs. The model involves a dialog authoring notation, based on concepts from programming languages, for specifying a variety of unsolicited reporting, mixed-initiative dialogs in a concise representation that serves as a design for dialog implementation. Guided by this foundation, we built a dialog staging engine which operationalizes dialogs specified in this notation. The model, notation, and engine help automate the engineering of mixed-initiative dialog systems. These results also provide a proof-of-concept for dialog specification and implementation from the perspective of theoretical programming languages. The ubiquity of dialogs in domains such as travel, education, and health care with the increased use of interactive voice-response systems and virtual environments provide a fertile landscape for further investigation of these results