Multimodal User Interaction in Smart Environments: Delivering Distributed User Interfaces

Blumendorf, Marco; Feuerstack, Sebastian; Albayrak, Şahin

doi:10.1007/978-3-540-85379-4_14

Cited by 8 publications

(8 citation statements)

References 8 publications

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“…Interactions received via one of the modalities are interpreted and mapped onto domain object manipulations or task completions. In combination with interaction channels [1] that can be set up to interaction devices on the fly to render and transport the results of the templates, task completions and object manipulations are reflected in all active presentations, which allows the synchronization of the different monomodal UI parts via the underlying model. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.…”

Section: The Multi-access Service Platformmentioning

confidence: 99%

Multimodal user interfaces for smart environments

Blumendorf

Feuerstack

Albayrak

2008

Proceedings of the Working Conference on Advanced Visual Interfaces

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User interface modeling is a well accepted approach to handle increasing user interface complexity. The approach presented in this paper utilizes user interface models at runtime to provide a basis for user interface distribution and synchronization. Task and domain model synchronize workflow and dynamic content across devices and modalities. A cooking assistant serves as example application to demonstrate multimodality and distribution. Additionally a debugger allows the inspection of the underlying user interface models at runtime.

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Section: The Multi-access Service Platformmentioning

confidence: 99%

Multimodal user interfaces for smart environments

Blumendorf

Feuerstack

Albayrak

2008

Proceedings of the Working Conference on Advanced Visual Interfaces

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“…MASP uses a model-driven approach to support: multimodality , distribution [Blumendorf et al 2007], synchronization , and adaptation [Schwartze et al 2009]. Although it demonstrates powerful capabilities in UI distribution and multimodality, we focus on its adaptation capabilities to stay within our scope.…”

Section: Layout Optimization Techniques 62mentioning

confidence: 99%

“…Adaptive UIs have been suggested for enhancing usability in these applications by catering to the variable user needs [Singh and Wesson 2009]. Many approaches were proposed for developing adaptive UIs targeting different types of software systems based on aspects such as: accessibility [Gajos et al 2010], concurrent tasks [Bihler and Mügge 2007], culture [Reinecke and Bernstein 2011], natural context [Blumendorf et al 2007], platform [Demeure et al 2008], etc. Other aspects such as: mental workload [Byrne and Parasuraman 1996] and cognition [Solovey et al 2011] were discussed in non-technical works and could be targeted by future systems.…”

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confidence: 99%

Adaptive Model-Driven User Interface Development Systems

2014

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Adaptive user interfaces (UIs) were introduced to address some of the usability problems that plague many software applications. Model-driven engineering formed the basis for most of the systems targeting the development of such UIs. An overview of these systems is presented and a set of criteria is established to evaluate the strengths and shortcomings of the state-of-the-art, which is categorized under architectures, techniques, and tools. A summary of the evaluation is presented in tables that visually illustrate the fulfillment of each criterion by each system. The evaluation identified several gaps in the existing art and highlighted the areas of promising improvement. The user interface (UI) layer is considered one of the key components of software applications since it connects their end-users to the functionality. Well-engineered and robust software applications could eventually fail to be adopted due to a weak UI layer. Some user interface development techniques such as: universal design [Mace et al. 1990], inclusive design [Keates et al. 2000], and design for all [Stephanidis 1997] promote the concept of making one UI design fit as many people as possible. Yet, a UI is not independent from its context-of-use, which is defined in terms of the user, platform, and environment [Calvary et al. 2003]. The "one design fits all" approach is unable to accommodate all the cases of variability in the context-of-use, in many cases leading to a diminished user experience. Building multiple UIs for the same functionality due to context variability is difficult since the scope of variability cannot be completely known at design-time and there is a high cost incurred by manually developing multiple versions of the UI. Adaptive UIs have been promoted as a solution for context variability due to their ability to automatically adapt to the context-of-use at runtime. User interfaces capable of adapting to their context-of-use are also referred to as multi-context or multi-target [Fonseca 2010]. A key goal behind adaptive UIs is plasticity denoting a UI's ability to preserve its usability across multiple contexts-of-use [Coutaz 2010]. Norcio and Stanley [1989] consider that the idea of an adaptive UI is straightforward since it simply means that: "The interface should adapt to the user; rather than the user adapting to the system" (p. 399) but they note that in spite of the simplicity of the definition, there are some difficult and complex problems relating to adaptive UIs. In our study of the literature, we noticed that some of these problems are technical and are related to devising systems that can support the development of adaptive UIs, while others are related to human factors such as the end-user acceptance of these UIs. Realizing the abstract properties illustrated in Fig. 1, could help in handling some of the technical and human problems related to adaptive UIs. Salehie and Tahvildari [2009] present a hierarchy of adaptability properties for software systems, referred to as self-* properties. This hierarchy demon...

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“…[5], dynamic adaptation of the VI to the context of use [6], [7], end-user programming [8], greater quality [9], [7], [10] and support generation [11], [12], [13] among others.…”

Section: Problem and Motivationmentioning

confidence: 99%

A multi-viewpoint approach to support collaborative user interface generation

Frey

Sottet

Vagner

2015

2015 IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

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Human-Computer Interaction (HCI) addresses the study, planning and design of the interaction between people and computers through Vser Interfaces (UIs). The co-design and co-development of these VIs involve different stakeholders as Devewpers, Functional Analysts, Usability Experts among others, all of them responsible for different VI elements (respectively implementation,Junctional requirements, usability). Collaboration between stakeholders has been identified as a key factor for VI design and development.

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Multimodal User Interaction in Smart Environments: Delivering Distributed User Interfaces

Cited by 8 publications

References 8 publications

Multimodal user interfaces for smart environments

Multimodal user interfaces for smart environments

Adaptive Model-Driven User Interface Development Systems

A multi-viewpoint approach to support collaborative user interface generation

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