Modeling the user state for context-aware spoken interaction in ambient assisted living

Ambient Assisted Living (AAL) systems must provide adapted services easily accessible by a wide variety of users. This can only be possible if the communication between the user and the system is carried out through an interface that is simple, rapid, effective, and robust. Natural language interfaces such as dialog systems fulfill these requisites, as they are based on a spoken conversation that resembles human communication. In this paper, we enhance systems interacting in AAL domains by means of incorporating context-aware conversational agents that consider the external context of the interaction and predict the user's state. The user's state is built on the basis of their emotional state and intention, and it is recognized by means of a module conceived as an intermediate phase between natural language understanding and dialog management in the architecture of the conversational agent. This prediction, carried out for each user turn in the dialog, makes it possible to adapt the system dynamically to the user's needs. We have evaluated our proposal developing a context-aware system adapted to patients suffering from chronic pulmonary diseases, and provide a detailed discussion of the positive influence of our proposal in the success of the interaction, the information and services provided, as well as the perceived quality.This work was supported in part by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02- 02, CAM CONTEXTS (S2009/TIC-1485

A Voice-based Mobile Prescription Application for Healthcare Services (VBMOPA)

Adverse drug effects are a major cause of death in the world with tens of thousand deaths occurring across the world each year because of medication or prescription errors. Many of such errors involve the administration of the wrong drug or dosage by care givers to patients due to indecipherable handwritings, drug interactions, confusing drug names etc. The adoption of voice-based mobile applications could eliminate some of these errors because they allow prescription information to be captured and heard through voice response rather than in the physician’s handwriting. This paper presents a design and implementation of a Voice-based Mobile Prescription Application (vbmopa) to improve health care services. The application can be accessed through a mobile phone by dialing an appropriate number. This system could lead to costs and life savings in healthcare centres across the world especially in developing countries where treatment processes are usually cumbersome and paper based

Conversational affective social robots for ageing and dementia support

Socially assistive robots (SAR) hold significant potential to assist older adults and people with dementia in human engagement and clinical contexts by supporting mental health and independence at home. While SAR research has recently experienced prolific growth, long-term trust, clinical translation and patient benefit remain immature. Affective human-robot interactions are unresolved and the deployment of robots with conversational abilities is fundamental for robustness and humanrobot engagement. In this paper, we review the state of the art within the past two decades, design trends, and current applications of conversational affective SAR for ageing and dementia support. A horizon scanning of AI voice technology for healthcare, including ubiquitous smart speakers, is further introduced to address current gaps inhibiting home use. We discuss the role of user-centred approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarise the state of development in interactions using speech and natural language processing, which forms a baseline for longitudinal health monitoring and cognitive assessment. Drawing from this foundation, we identify open challenges and propose future directions to advance conversational affective social robots for: 1) user engagement, 2) deployment in real-world settings, and 3) clinical translation

Improving and Evaluating eMMA's Communication Skills: A Chatbot for Managing Medication

In previous work, a mobile application for medication self-management (eMMA) was introduced. It contained a basic conversational user interface (CUI). In this work, we extended the CUI by integrating the chatbot framework RiveScript and an instruction interface. To study task success, dialog quality and efficiency, we performed a theoretical and a quantitative evaluation as well as a usability test. The results show that the technical extensions of eMMA were useful to improve the chatbot's quality. However, the underlying knowledge base still requires substantial extensions before the system can be used in practice

Synchronization in an Asynchronous Agent-based Architecture for Dialogue Systems

Most dialogue architectures are either pipelined or, if agent-based, are restricted to a pipelined flow-of-information. The TRIPS dialogue architecture is agent-based and asynchronous, with several layers of information flow. We present this architecture and the synchronization issues we encountered in building a truly distributed, agentbased dialogue architecture

One Size Does Not Fit All: Meeting the Health Care Needs of Diverse Populations

Proposes a framework for meeting patients' cultural and linguistic needs: policies and procedures that support cultural competence, data collection, population-tailored services, and internal and external collaborations. Includes a self-assessment tool