A Multi-channel Application Framework for Customer Care Service Using Best-First Search Technique

It has become imperative to find a solution to the dissatisfaction in response by mobile service providers when interacting with their customer care centres. Problems faced with Human to Human Interaction (H2H) between customer care centres and their customers include delayed response time, inconsistent solutions to questions or enquires and lack of dedicated access channels for interaction with customer care centres in some cases. This paper presents a framework and development techniques for a multi-channel application providing Human to System (H2S) interaction for customer care centre of a mobile telecommunication provider. The proposed solution is called Interactive Customer Service Agent (ICSA). Based on single-authoring, it will provide three media of interaction with the customer care centre of a mobile telecommunication operator: voice, phone and web browsing. A mathematical search technique called Best-First Search to generate accurate results in a search environmen

Sound for enhanced experiences in mobile applications

When visiting new places you want information about restaurants, shopping, places of historic in- terest etc. Smartphones are perfect tools for de- livering such location-based information, but the risk is that users get absorbed by texts, maps, videos etc. on the device screen and get a second- hand experience of the environment they are vis- iting rather than the sought-after first-hand expe- rience. One problem is that the users’ eyes often are directed to the device screen, rather than to the surrounding environment. Another problem is that interpreting more or less abstract informa- tion on maps, texts, images etc. may take up sig- nificant shares of the users’ overall cognitive re- sources. The work presented here tried to overcome these two problems by studying design for human-computer interaction based on the users’ everyday abilities such as directional hearing and point and sweep gestures. Today’s smartphones know where you are, in what direction you are pointing the device and they have systems for ren- dering spatial audio. These readily available tech- nologies hold the potential to make information more easy to interpret and use, demand less cog- nitive resources and free the users from having to look more or less constantly on a device screen

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

Staging Transformations for Multimodal Web Interaction Management

Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.Comment: Describes framework and software architecture for multimodal web interaction managemen

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

Vision systems with the human in the loop

The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed

Symbol Emergence in Robotics: A Survey

Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic