On the Development of Adaptive and User-Centred Interactive Multimodal Interfaces

Multimodal systems have attained increased attention in recent years, which has made possible important improvements in the technologies for recognition, processing, and generation of multimodal information. However, there are still many issues related to multimodality which are not clear, for example, the principles that make it possible to resemble human-human multimodal communication. This chapter focuses on some of the most important challenges that researchers have recently envisioned for future multimodal interfaces. It also describes current efforts to develop intelligent, adaptive, proactive, portable and affective multimodal interfaces

Providing personalized Internet services by means of context-aware spoken dialogue systems

The widespread use of new mobile technology implementing wireless communications enables a new type of advanced applications to access information services on the Internet. In order to provide services which meet the user needs through intelligent information retrieval, the system must sense and interpret the user environment and the communication context. Though context-awareness is vital to provide services adapted to the user preferences, it cannot be useful if such services are difficult to access. The development of spoken dialogue systems for these applications facilitates interaction in natural language with the environment which is also benefited from contextual information. In this paper, we propose a framework to develop context-aware dialogue systems that dynamically incorporate user specific requirements and preferences as well as characteristics about the interaction environment, in order to improve and personalize web information and services. We have identified the major components for context-aware dialogue systems and placed them within a general-purpose architecture. The framework also describes a representation mode based on a dialogue register in order to share information between the elements of the architecture, and incorporates statistical methodologies for dialogue management in order to reduce the effort required for both the implementation of a new system and the adaptation to a new task. We have evaluated our proposal developing a travel-planning system, and provide a detailed discussion of its positive influence in the quality of the interaction and the information and services provided.Research funded by projects CICYT TIN2011- 28620-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485), and DPS2008- 07029-C02-02.Publicad

Bringing context-aware access to the web through spoken interaction

The web has become the largest repository of multimedia information and its convergence with telecommunications is now bringing the benefits of web technology to hand-held devices. To optimize data access using these devices and provide services which meet the user needs through intelligent information retrieval, the system must sense and interpret the user environment and the communication context. In addition, natural spoken conversation with handheld devices makes possible the use of these applications in environments in which the use of GUI interfaces is not effective, provides a more natural human-computer interaction, and facilitates access to the web for people with visual or motor disabilities, allowing their integration and the elimination of barriers to Internet access. In this paper, we present an architecture for the design of context-aware systems that use speech to access web services. Our contribution focuses specifically on the use of context information to improve the effectiveness of providing web services by using a spoken dialog system for the user-system interaction. We also describe an application of our proposal to develop a context-aware railway information system, and provide a detailed evaluation of the influence of the context information in the quality of the services that are supplied.Research funded by projects CICYT TIN2011-28620-C02-01, CICYT TEC 2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun

Combining heterogeneous inputs for the development of adaptive and multimodal interaction systems

In this paper we present a novel framework for the integration of visual sensor networks and speech-based interfaces. Our proposal follows the standard reference architecture in fusion systems (JDL), and combines different techniques related to Artificial Intelligence, Natural Language Processing and User Modeling to provide an enhanced interaction with their users. Firstly, the framework integrates a Cooperative Surveillance Multi-Agent System (CS-MAS), which includes several types of autonomous agents working in a coalition to track and make inferences on the positions of the targets. Secondly, enhanced conversational agents facilitate human-computer interaction by means of speech interaction. Thirdly, a statistical methodology allows modeling the user conversational behavior, which is learned from an initial corpus and improved with the knowledge acquired from the successive interactions. A technique is proposed to facilitate the multimodal fusion of these information sources and consider the result for the decision of the next system action.This work was supported in part by Projects MEyC TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS S2009/TIC-1485Publicad

A novel approach for data fusion and dialog management in user-adapted multimodal dialog systems

Proceedings of: 17th International Conference on Information Fusion (FUSION 2014): Salamanca, Spain 7-10 July 2014.Multimodal dialog systems have demonstrated a high potential for more flexible, usable and natural humancomputer interaction. These improvements are highly dependent on the fusion and dialog management processes, which respectively integrates and interprets multimedia multimodal information and decides the next system response for the current dialog state. In this paper we propose to carry out the multimodal fusion and dialog management processes at the dialog level in a single step. To do this, we describe an approach based on a statistical model that takes user's intention into account, generates a single representation obtained from the different input modalities and their confidence scores, and selects the next system action based on this representation. The paper also describes the practical application of the proposed approach to develop a multimodal dialog system providing travel and tourist information.This work was supported in part by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485).Publicad

Multi-Agent System (MAS) Applications in Ambient Intelligence (AmI) Environments

Proceedings of: 8th Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS`10). Salamanca (Spain), 28-30 April 2010Research in context-aware systems has been moving towards reusable and adaptable architectures for managing more advanced human-computer interfaces. Ambient. Intelligence (AmI) investigates computer-based services, which are ubiquitous and based on a variety of objects and devices. Their intelligent and intuitive interfaces act as mediators through which people can interact with the ambient environment. In this paper we present an agent-based architecture which supports the execution of agents in AmI environments. Two case studies are also presented, an airport information system and a railway information system, which uses spoken conversational agents to respond to the user's requests using the contextual information that includes the location information of the user.This work has been partially supported by CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008-07029-C02-02Publicad

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