Search

To test whether the language we speak influences our behavior even when we are not speaking, we asked speakers of four languages differing in their predominant word orders (English, Turkish, Spanish, and Chinese) to perform two nonverbal tasks: a communicative task (describing an event by using gesture without speech) and a noncommunicative task (reconstructing an event with pictures). We found that the word orders speakers used in their everyday speech did not influence their nonverbal behavior. Surprisingly, speakers of all four languages used the same order and on both nonverbal tasks. This order, actor--patient--act, is analogous to the subject--object--verb pattern found in many languages of the world and, importantly, in newly developing gestural languages. The findings provide evidence for a natural order that we impose on events when describing and reconstructing them nonverbally and exploit when constructing language anew. gesture | language genesis | sign language | word order

Research in automatic analysis of sign language has largely focused on recognizing the lexical (or citation) form of sign gestures as they appear in continuous signing, and developing algorithms that scale well to large vocabularies. However, successful recognition of lexical signs is not sufficient for a full understanding of sign language communication. Nonmanual signals and grammatical processes which result in systematic variations in sign appearance are integral aspects of this communication but have received comparatively little attention in the literature. In this survey, we examine data acquisition, feature extraction and classification methods employed for the analysis of sign language gestures. These are discussed with respect to issues such as modeling transitions between signs in continuous signing, modeling inflectional processes, signer independence, and adaptation. We further examine works that attempt to analyze nonmanual signals and discuss issues related to integrating these with (hand) sign gestures. We also discuss the overall progress toward a true test of sign recognition systems--dealing with natural signing by native signers. We suggest some future directions for this research and also point to contributions it can make to other fields of research. Web-based supplemental materials (appendicies) which contain several illustrative examples and videos of signing can be found at www.computer.org/publications/dlib. Index Terms--Sign language recognition, hand tracking, hand gesture recognition, gesture analysis, head tracking, head gesture recognition, face tracking, facial expression recognition, review.

We present a hand and face segmentation methodology using color and motion cues for the content-based representation of sign language video sequences. The methodology consists of three stages, namely skin-color segmentation, change detection, and face and hand segmentation mask generation. In skin-color segmentation, a universal color-model is derived and image pixels are classified as skin or nonskin based on their Mahalanobis distance. We derive a segmentation threshold for the classifier. The aim of change detection is to localize moving objects in a video sequences. The change detection technique is based on the F test and block-based motion estimation. Finally, the results from skin-color segmentation and change detection are analyzed to segment the face and hands. The performance of the algorithm is illustrated by simulations carried out on standard test sequences. Index Terms--Change detection, sign language, skin-color segmentation, video segmentation.

We present an algorithm for extracting and classifying two-dimensional motion in an image sequence based on motion trajectories. First, a multiscale segmentation is performed to generate homogeneous regions in each frame. Regions between consecutive frames are then matched to obtain two-view correspondences. Affine transformations are computed from each pair of corresponding regions to define pixel matches. Pixels matches over consecutive image pairs are concatenated to obtain pixel-level motion trajectories across the image sequence. Motion patterns are learned from the extracted trajectories using a time-delay neural network. We apply the proposed method to recognize 40 hand gestures of American Sign Language. Experimental results show that motion patterns of hand gestures can be extracted and recognized accurately using motion trajectories. Index Terms--Motion segmentation, motion analysis, motion trajectory, American Sign Language, hand gesture recognition, time-delay neural network.

Byline: John T.E. Richardson (1), Alan Woodley (2) Keywords: approaches to studying; Approaches to Studying Inventory; deaf students; distance education; hearing loss; sign language Abstract: This investigation examined approaches to studyingamong deaf students taking courses by distance learning whopreferred to communicate using either sign language or spokenlanguage. In comparison with hearing students, the deaf studentsobtained higher scores on comprehension learning, surfaceapproach, improvidence and fear of failure. Whilst they obtainedhigher scores on reproducing orientation, their qualitativeresponses indicated that this was not because they had beendriven to use rote memorisation. In addition, the deaf studentsseemed just as capable as the hearing students of adopting ameaning orientation. In the specific context of distanceeducation, there were no differences in approaches to studyingrelated to the students' preferred mode of communication.However, communicating by sign language rather than speech haddifferent practical consequences for the students' effectiveworkload. Author Affiliation: (1) Department of Human Sciences, Brunel University, Uxbridge, Middlesex, UB8 3PH, U.K. (2) Institute of Educational Technology, The Open University, Walton Hall, Milton Keynes, MK7 6AA, U.K. Article History: Registration Date: 10/10/2004

We present two real-time hidden Markov model-based systems for recognizing sentence-level continuous American Sign Language (ASL) using a single camera to track the user's unadorned hands. The first system observes the user from a desk mounted camera and achieves 92 percent word accuracy. The second system mounts the camera in a cap worn by the user and achieves 98 percent accuracy (97 percent with an unrestricted grammar). Both experiments use a 40-word lexicon. Index Terms - Gesture recognition, hidden Markov models, wearable computers, sign language, motion and pattern analysis.

Some researchers do not agree to the universality of the leftward WH-movement in American sign language (ASL) and stress that it should be to the right. Others, however, claim that the use of WH-elements in sentence- or discourse-final positions proves that the WH-movement is a leftward specifier of CP and is not rightward. This is also validated by cross-linguistic generalizations and the use of direct and indirect WH-questions in ASL.

Gesture has been a topic of interest since antiquity because of its relevance to theoretical issues in cognition, language acquisition and conversational processes. Through microanalysis, speech and bodily movements are found to be produced together, thus, becoming two aspects of a single process. Furthermore, recognition of cultural differences in gestures are observed which stem from language differences and influenced by cultural values and historical traditions.

The left hemisphere of the brain dominates acquisition and use of both spoken and sign language. Sign language users with brain lesions on one side show left hemisphere dominance despite the dependence of sign language on visuo-spatial processible rather than temporal information. Both sign and spoken languages are highly structure systems and their neural organization in the hemispheres is identical. This indicates that the left hemisphere dominance is due to a higher-property of the language system rather than its physical characteristics or motor production.

A KEY FEATURE OF HUMAN DEVELOPMENT is the regular onset of vocal babbling well before infants are able to utter recognizable words [1]. Vocal babbling is widely recognized as being [...]

Recent research has examined the early stages of language development in signed and spoken language. In this paper we discuss claims that, in the timing of early language milestones, there is an advantage for the acquisition of signed languages. In particular, we will review the evidence that the emergence of the first signs and of the first two-sign combinations is precocious in signing children as compared to the appearance of the first words and of the first two-word strings in speaking children. We conclude that the evidence for early emergence of the first signs deserves continued attention, but that the evidence for early syntax in signing children is not at all compelling. Finally, we discuss the import of a short-lived sign advantage in early language acquisition, in terms of understanding maturational timing mechanisms more generally. Specifically, we address the question of whether or not a single timing mechanism underlies early milestones in the acquisition of both vocabulary and syntax.

Ted Supalla, an associate professor of linguistics, and Elissa Newport, a professor of psychology at the University of Rochester's Sign Language Research Center, are analyzing sign language to find out universal linguistic principles and analyze the evolution of languages. Their research includes examining the verbs of sign languages and searching for proof that languages can be learned more efficiently during a particular period in childhood and early adolescence. Sign language and spoken language are generated in the same parts of the brain.

Anthropological researchers have tended to treat deaf people as marked more by pathology than behavior. However, recent studies of deafness have investigated issues of language ideology, community identity, and its formation and maintenance.

Nicaraguan deaf students have created a new sign language, and it has fueled the debate among linguists over how languages are formed When Nicaragua established a school for the deaf [...]

It has long been postulated that language is not purely learned, but arises from an interaction between environmental exposure and innate abilities. The innate component becomes more evident in rare situations in which the environment is markedly impoverished. The present study investigated the language production of a generation of deaf Nicaraguans who had not been exposed to a developed language. We examined the changing use of early linguistic structures (specifically, spatial modulations) in a sign language that has emerged since the Nicaraguan group first came together. In under two decades, sequential cohorts of learners systematized the grammar of this new sign language. We examined whether the systematicity being added to the language stems from children or adults; our results indicate that such changes originate in children aged 10 and younger. Thus, sequential cohorts of interacting young children collectively possess the capacity not only to learn, but also to create, language.

The upper regions of the temporal lobe of the brain are important in hearing and comprehension of spoken language. The regions have been shown to be activated by sign language in congenitally deaf subjects, suggesting that the brain region for hearing could be activated by other sensory modalities, providing evidence of neural plasticity. Sign language was found to activate the 'language' areas, although not primary auditory cortex, and the sign language area was identified as the supratemporal gyri.

The critique by Petronio and Lillo-Martin 1997 of the argument that, in American sign language (ASL), WH-phases move rightward to a specifier CP position, proposes a leftward WH-movement. A new study suggests that Petronio and Lillo-Martin incorrectly interpreted the data and their analysis does not account for the facts of the language. Therefore, the argument that ASL WH-phases move to the right in ASL holds good.