Grammar Generation and Optimization from Multiple Inputs

Human being uses multiple modes like speech, text, facial expression, hand gesture, showing picture etc. for communication in between them. The use of this ways for communication makes human communication more simple and fast. In previous years several techniques are used to bring the human computer interaction more closely. It costs more for development and maintenance of Multimodal grammar in integrating and understanding input in multimodal interfaces i.e. using multiple input ways. This leads to improve and investigate more robust algorithm. The proposed system generates the grammar from multiple inputs called as multimodal grammar and evaluates grammar description length. Furthermore, to optimize the multimodal grammar proposed system uses learning operators which improves grammar description DOI: 10.17762/ijritcc2321-8169.15016

Interface, multimodal / multisensory

International audienceIn general, a multimodal interface is a class of interfaces, designed to make the interaction process between a human and a computer more similar to human-to-human communication. What is important in a multimodal interface, is that these kinds of systems strive for meaning, as defined in multimodality from the point of view of HCI

Computers that smile: Humor in the interface

It is certainly not the case that wen we consider research on the role of human characteristics in the user interface of computers that no attention has been paid to the role of humor. However, when we compare efforts in this area with efforts and experiments that attempt to demonstrate the positive role of general emotion modelling in the user interface, then we must conclude that this attention is still low. As we all know, sometimes the computer is a source of frustration rather than a source of enjoyment. And indeed we see research projects that aim at recognizing a user’s frustration, rather than his enjoyment. However, rather than detecting frustration, and maybe reacting on it in a humorous way, we would like to prevent frustration by making interaction with a computer more natural and more enjoyable. For that reason we are working on multimodal interaction and embodied conversational agents. In the interaction with embodied conversational agents verbal and nonverbal communication are equally important. Multimodal emotion display and detection are among our advanced research issues, and investigations in the role of humor in human-computer interaction is one of them

How are translations created? Using multimodal conversation analysis to study a team translation process

This article demonstrates a methodology for studying the translation process from the perspective of multimodal social interaction and applies this methodology to a case analysis of collaborative audio description. The methodology is multimodal conversation analysis, which aims to uncover the way in which multimodal communication resources (e.g., talk, gaze, gestures) are used holistically and situatedly in building human action. Being empirical and data-driven, multimodal conversation analysis observes human conduct in its natural setting. This article analyses video data from an authentic audio-description process and presents the multimodal constitution of problem-solving sequences duringtranslating. In addition, the article discusses issues regarding the methodological choices facing researchers who are interested in human interaction in translation. The article shows that applying multimodal conversation analysis opens new avenues for research into the translation process and collaborative translation.Peer reviewe