Articulatory Phonology views speech as an ensemble of constricting events (e.g. narrowing lips, raising tongue tip), gestures, at distinct organs (lips, tongue tip, tongue body, velum, and glottis) along the vocal tract. This study shows that articulatory information in the form of gestures and their output trajectories (tract variable time functions or TVs) can help to improve the performance ...

This paper tackles a new prototype of dynamic hand gestures and its advantages to apply in controlling smart home appliances. The proposed gestures convey cyclical patterns of hand shapes as well hand movements. Thanks to the periodicity of defined gestures, on one hand, some common technical issues that may appear when deploying the application (e.g., spotting gestures from a video stream) are...

We propose a fully automatic method for learning gestures on big touch devices in a potentially multi-user context. The goal is to learn general models capable of adapting to different gestures, user styles and hardware variations (e.g. device sizes, sampling frequencies and regularities). Based on deep neural networks, our method features a novel dynamic sampling and temporal normalization com...

An architecture for opportunistic discovery of gesture elements for analysis of human gestures in a multi-camera sensor network is presented in this paper. The proposed approach is motivated by the diversity of gestures expressed in passive monitoring applications, and is based on the concept of opportunistic fusion of simple features within a single camera and active collaboration between mult...

Human communication always used gestures, movements and expressions as oral language support. Certain gestures are so commonly used around the world that are understood throughout different cultures and times, such as a wave or thumbs up. Natural Interaction is a way to apply this concept to user interfaces in computer systems. In this paper we discuss about the use of Natural Interaction featu...

Gesture is a non-verbal modality that can contribute crucial information to the understanding of natural language. But not all gestures are informative, and non-communicative hand motions may confuse natural language processing (NLP) and impede learning. People have little difficulty ignoring irrelevant hand movements and focusing on meaningful gestures, suggesting that an automatic system coul...

The objective of the gesture recognition is to identify and distinguish the human gestures and utilizes these identified gestures for applications in specific domain. In this paper we propose a new approach to build a real time system to identify the standard gesture given by American Sign Language, or ASL, the dominant sign language of Deaf Americans, including deaf communities in the United S...

The goal of this project is to have the telepresence robot recognize and follow military hand signals. These signals consist of commands such as Halt, Crawl Forward, Run Forward, Retreat, Flank Left/Right, etc. Upon recognizing a gesture the robot will execute a hardcoded response. The robot will be equipped with a Kinect sensor that detects the skeleton of a human. We have also coded a baselin...

Most models of speech planning and production incorporate a selection mechanism, whereby units are activated in parallel and chosen for execution sequentially. The lowest level units which can be selected are assumed to be segments, i.e. consonants and vowels. The features or articulatory gestures affiliated with segments are presumed to be automatically selected as a consequence of segmental s...

In this work we present a method to detect and recognize the signs of the card game of Truco which are a subset of facial gestures. The method uses temporal templates to represent motion and later extract features. The proposed method works in real time, allowing to use it as an human-computer interface , for example, in the context of the card game of Truco . To the best of our knowledge this ...