This paper introduces a method that generates simulated multimodal input to be used in testing multimodal system implementations, as well as to build statistically motivated multimodal integration modules. The generation of such data is inspired by the fact that true multimodal data, recorded from real usage scenarios, is difficult and costly to obtain in large amounts. On the other hand, thank...

The application of statistical learning to multimodal signal processing requires a significant amount of data for development, training and test. The availability of data often conditions the possibility of an investigation, and can influence its objectives and application domains. The development of innovative multimodal signal processing methods depends not only on raw data recorded from vari...

The growing emphasis on multimodal interface design is fundamentally inspired by the aim to support natural, flexible, efficient, and powerfully expressive means of human-computer interaction that are easy to learn and use. Multimodal interfaces represent a new direction for computing that draws from the myriad input and output technologies becoming available, and that potentially can integrate...

In the context of pervasive environments, multimodal interaction plays a pivotal role because multimodality provides flexibility and naturalness for interaction. The challenge of multimodal interfaces in pervasive environments is then to build reliable and autonomic processing systems able to analyze and understand multiple interaction modalities and reconfigure itself in real-time. Addressing ...

Future interaction will be embedded into smart environments offering the user to choose and to combine a heterogeneous set of interaction devices and modalities based on his preferences realizing an ubiquitous and multimodal access. We propose a model-based runtime environment (the MINT Framework) that describes multimodal interaction by interactors and multimodal mappings. The interactors are ...

In order to realize their full potential, multimodal systems need to support not just input from multiple modes, but also synchronized integration of modes. Johnston et al (1997) model this integration using a unification operation over typed feature structures. This is an effective solution for a broad class of systems, but limits multimodal utterances to combinations of a single spoken phrase...

In earlier days Traditional authentication method in computer systems are based on knowledge and token based. Unfortunately lot of drawbacks are in these systems. Passwords often be forgotten, disclosed or changed. A reliable and accurate identification/verification technique may be designed by Biometrics technologies. In Biometrics field there are two types of technologies are present. Unimode...

Two requirements should be met in order to develop a practical multimodal interface system, i.e., (1) integration of delayed arrival of data, and (2) elimination of ambiguity in recognition results of each modality. This paper presents an e cient and generic methodology for interpretation of multimodal input to satisfy these requirements. The proposed methodology can integrate delayed-arrival d...

Automatic detection of aggressive situations has a high societal and scientific relevance. It has been argued that using data from multimodal sensors as for example video and sound as opposed to unimodal is bound to increase the accuracy of detections. We approach the problem of multimodal aggression detection from the viewpoint of a human observer and try to reproduce his predictions automatic...

Natural interaction in multimodal dialogue systems demands quick system response after the end of a user turn. The prediction of the end of user input at each multimodal dialog turn is complicated as users can interact through modalities in any order, and convey a variety of different messages to the system within the turn. Several multimodal interaction frameworks have used fixed-duration time...