Multimodal, immersive, virtual reality (VR) techniques open new perspectives for perceptual-motor skill trainers. They also introduce new risks and dangers. This paper describes the benefits and pitfalls of multimodal training and the cognitive building blocks of a multimodal, VR training simulators.

In this paper we introduceBiosignalsStudio (BSS), a framework for multimodal sensor data acquisition. Due to its flexible architecture it can be used for large scale multimodal data collections as well as a multimodal input layer for intelligent systems. The paper describes the software framework and its contributions to our research work and

 Understand how the diverse mechanisms of cancer cachexia; mean that a multimodal therapeutic approach is necessary;  Understand the need to develop more sensitive/robust outcomes for cachexia therapy;  Understand basic assessment of patients with cancer cachexia;  Understand the elements that make up a multimodal approach to the management of cancer cachexia;  Understand the issues of com...

We propose in this paper a broad-coverage approach for multimodal annotation of conversational data. Large annotation projects addressing the question of multimodal annotation bring together many different kinds of information from different domains, with different levels of granularity. We present in this paper the first results of the OTIM project aiming at developing conventions and tools fo...

In recent years, data-driven methods have become increasingly popular in natural language generation. Multimodal generation can also benefit from using corpus data directly; however, there are several issues that arise when using corpora for multimodal generation that do not occur in the unimodal case, and that mean that existing multimodal corpora are often not suitable for being directly used...

The SIDGrid architecture provides a framework for distributed annotation, archiving, and analysis of the rapidly growing volume of multimodal data. The framework integrates three main components: an annotation and analysis client, a web-accessible data repository, and a portal to the distributed processing capability of the TeraGrid. The architecture provides both a novel integration of annotat...

Biometric recognition is automated recognition of individual based on the physiological and behavioral characteristics. Unimodal biometrics are facing problems like noisy data, intra class variation, inter class variation, spoofing attack etc. These limitations can be solved by using multimodal biometrics. Comparing to unimodal, multimodal biometric systems are performing better. A multimodal b...

Finding useful information from large multimodal document collections such as the WWW is one of the major challenges of Information Retrieval (IR). The many sources of information now available text, images, audio, video and more increases the need for multimodal search. Particularly important is also the recognition, that each information item is inherently multimodal (i.e. has aspects in its ...

In this paper we describe an implemented framework for releasing multimodal corpora as Linked Data. In particular, we describe our experiences in releasing a multimodal corpus based on an online chat game as Linked Data. Building on an internal multimodal data model we call FiESTA, we have implemented a library that enhances existing libraries and classes by functionality allowing to convert th...

We present a flexible framework for multimodal engineering applications using augmented reality. Our goal is to simplify the configuration procedures and to provide a higher grade of flexibility in multimodal interfaces. The system architecture is based on an extensible plug-in approach. A specific component has been designed to manage and synchronize the different multimodal inputs. A configur...