Using Sound to Enhance Users’ Experiences of Mobile Applications

The latest smartphones with GPS, electronic compass, directional audio, touch screens etc. hold potentials for location based services that are easier to use compared to traditional tools. Rather than interpreting maps, users may focus on their activities and the environment around them. Interfaces may be designed that let users search for information by simply pointing in a direction. Database queries can be created from GPS location and compass direction data. Users can get guidance to locations through pointing gestures, spatial sound and simple graphics. This article describes two studies testing prototypic applications with multimodal user interfaces built on spatial audio, graphics and text. Tests show that users appreciated the applications for their ease of use, for being fun and effective to use and for allowing users to interact directly with the environment rather than with abstractions of the same. The multimodal user interfaces contributed significantly to the overall user experience

Testing Two Tools for Multimodal Navigation

The latest smartphones with GPS, electronic compasses, directional audio, touch screens, and so forth, hold a potential for location-based services that are easier to use and that let users focus on their activities and the environment around them. Rather than interpreting maps, users can search for information by pointing in a direction and database queries can be created from GPS location and compass data. Users can also get guidance to locations through point and sweep gestures, spatial sound, and simple graphics. This paper describes two studies testing two applications with multimodal user interfaces for navigation and information retrieval. The applications allow users to search for information and get navigation support using combinations of point and sweep gestures, nonspeech audio, graphics, and text. Tests show that users appreciated both applications for their ease of use and for allowing users to interact directly with the surrounding environment

Machine Understanding of Human Behavior

A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior

Follow-up question handling in the IMIX and Ritel systems: A comparative study

One of the basic topics of question answering (QA) dialogue systems is how follow-up questions should be interpreted by a QA system. In this paper, we shall discuss our experience with the IMIX and Ritel systems, for both of which a follow-up question handling scheme has been developed, and corpora have been collected. These two systems are each other's opposites in many respects: IMIX is multimodal, non-factoid, black-box QA, while Ritel is speech, factoid, keyword-based QA. Nevertheless, we will show that they are quite comparable, and that it is fruitful to examine the similarities and differences. We shall look at how the systems are composed, and how real, non-expert, users interact with the systems. We shall also provide comparisons with systems from the literature where possible, and indicate where open issues lie and in what areas existing systems may be improved. We conclude that most systems have a common architecture with a set of common subtasks, in particular detecting follow-up questions and finding referents for them. We characterise these tasks using the typical techniques used for performing them, and data from our corpora. We also identify a special type of follow-up question, the discourse question, which is asked when the user is trying to understand an answer, and propose some basic methods for handling it