In sign languages of the deaf some signs can meaningfully point toward things or can be meaningfully placed in the space ahead of the signer. This obligatory part of fluent grammatical signing has no ...parallel in vocally produced languages. This book focuses on American Sign Language to examine the grammatical and conceptual purposes served by these directional signs. It guides the reader through ASL grammar, the different categories of directional signs, the types of spatial representations signs are directed toward, how such spatial conceptions can be represented in mental space theory, and the conceptual purposes served by these signs. The book demonstrates a remarkable integration of grammar and gesture in the service of constructing meaning. These results also suggest that our concept of 'language' has been much too narrow and that a more comprehensive look at vocally produced languages will reveal the same integration of gestural, gradient, and symbolic elements.
The Routledge Handbook of Theoretical and Experimental Sign Language Research bridges the divide between theoretical and experimental approaches to provide an up-to-date survey of key topics in sign ...language research. With 29 chapters written by leading and emerging scholars from around the world, this Handbook covers the following key areas:
On the theoretical side, all crucial aspects of sign language grammar studied within formal frameworks such as Generative Grammar;
Each chapter features an introduction, an overview of existing research, and a critical assessment of hypotheses and findings. The Routledge Handbook of Theoretical and Experimental Sign Language Research is key reading for all advanced students and researchers working at the intersection of sign language research, linguistics, psycholinguistics, and neurolinguistics.
On the experimental side, theoretical accounts are supplemented by experimental evidence gained in psycho- and neurolinguistic studies;
On the descriptive side, the main phenomena addressed in the reviewed scholarship are summarized in a way that is accessible to readers without previous knowledge of sign languages.
We are pleased to present a Special Issue of Languages on the topic of Sign Language Emergence. Sign languages are the only extant languages that can be caught in the act of being born and developing ...with no model, and they, therefore, offer the only empirical evidence for language emergence in human societies. We have brought together a collection of articles on emerging sign languages that contribute a great deal to our current understanding of this process.This Special Issue covers eleven different emerging sign languages around the world. The articles deal with several aspects of language emergence, including, most notably: (1) the relationship between the emerging language and the culture of the larger society; (2) the role of iconicity in the emergence of sign language; (3) the relationship between the shared context in a small signing community and the degree of variation in the vocabulary; and (4) the vulnerability of budding sign languages. Spoken creole languages are also young, but are different from emerging sign languages, in that the speakers of pidgins from which creoles are assumed to have descended already had native languages. One article compares the features of creoles and of emerging sign languages.We are especially pleased with the diversity and breadth of interests of the contributors to the volume, who are based on four continents. The languages that they cover are equally diverse in their geographical provenance.
Wayfinding signs must have prominent visibility in the environment to provide people with the information they need to navigate to an intended destination. Therefore, designers seek to design signs ...that are clearly visible while esthetically harmonious with the ambient environment. To find highly conspicuous colors, 1632 images showing combinations of various colors and environments were created. And then evaluation factors such as sign conspicuity, color contrast, color harmony, sign color preference, and expected sign usability were tested with 33 designers. Through statistical analysis of experimental results, the colors with high conspicuity and harmony were organized in different types of environments, and all correlations between the evaluation factors were analyzed. The results showed that all evaluation factors had a significantly high correlation except color harmony. Based on these results, we conclude that when designing a sign, it should focus on increasing the sign conspicuity by using color difference rather than color harmony between the sign and the ambient environment.
The meniscus is an organized collection of fibrocartilaginous tissue that is located between the femoral condyles and the tibial plateau of the knee which primarily assists with load transmission. ...The complex composition of articulating soft-tissue structures in the knee causes the menisci to become a common source of injury, especially in the realm of athletic trauma. Magnetic resonance imaging (MRI) has become the imaging modality of choice for evaluating patients with suspected meniscal pathology because of its numerous advantages over plain radiographs. Most forms of meniscal tears have classic MRI findings and are used in correlation with physical examination findings to confirm or rule out a diagnosis. These imaging findings are referred to as signs and have been well studied, and the associated eponyms for each sign are well published throughout the literature. This article will review and describe a unique selection of meniscal pathology as visualized by MRI that is more commonly published in musculoskeletal radiology literature when compared with orthopedics and sports medicine literature.
Traffic sign detection and recognition are crucial in the development of intelligent vehicles. An improved traffic sign detection and recognition algorithm for intelligent vehicles is proposed to ...address problems such as how easily affected traditional traffic sign detection is by the environment, and poor real-time performance of deep learning-based methodologies for traffic sign recognition. Firstly, the HSV color space is used for spatial threshold segmentation, and traffic signs are effectively detected based on the shape features. Secondly, the model is considerably improved on the basis of the classical LeNet-5 convolutional neural network model by using Gabor kernel as the initial convolutional kernel, adding the batch normalization processing after the pooling layer and selecting Adam method as the optimizer algorithm. Finally, the traffic sign classification and recognition experiments are conducted based on the German Traffic Sign Recognition Benchmark. The favorable prediction and accurate recognition of traffic signs are achieved through the continuous training and testing of the network model. Experimental results show that the accurate recognition rate of traffic signs reaches 99.75%, and the average processing time per frame is 5.4 ms. Compared with other algorithms, the proposed algorithm has remarkable accuracy and real-time performance, strong generalization ability and high training efficiency. The accurate recognition rate and average processing time are markedly improved. This improvement is of considerable importance to reduce the accident rate and enhance the road traffic safety situation, providing a strong technical guarantee for the steady development of intelligent vehicle driving assistance.
In recent years, the deep learning is applied to the field of traffic sign detection methods which achieves excellent performance. However, there are two main challenges in traffic sign detection to ...be solve urgently. For one thing, some traffic signs of small size are more difficult to detect than those of large size so that the small traffic signs are undetected. For another, some false signs are always detected because of interferences caused by the illumination variation, bad weather and some signs similar to the true traffic signs. Therefore, to solve the undetection and false detection, we first propose a cascaded R-CNN to obtain the multiscale features in pyramids. Each layer of the cascaded network except the first layer fuses the output bounding box of the previous one layer for joint training. This method contributes to the traffic sign detection. Then, we propose a multiscale attention method to obtain the weighted multiscale features by dot-product and softmax, which is summed to fine the features to highlight the traffic sign features and improve the accuracy of the traffic sign detection. Finally, we increase the number of difficult negative samples for dataset balance and data augmentation in the training to relieve the interference by complex environment and similar false traffic signs. The data augment method expands the German traffic sign training dataset by simulation of complex environment changes. We conduct numerous experiments to verify the effectiveness of our proposed algorithm. The accuracy and recall rate of our method are 98.7% and 90.5% in GTSDB, 99.7% and 83.62% in CCTSDB and 98.9% and 85.6% in Lisa dataset respectively.
Sign language learners with a spoken language background face the challenge of acquiring a second language in a different modality. In the course of this endeavor, one of the modality-specific ...phenomena they encounter is the use of classifier predicates, also known as depicting signs. Classifier predicates contain a meaningful hand configuration that refers to an entity, denoting a salient characteristic of this entity (Zwitserlood, 2003). The use of a classifier predicate allows the signer to indicate the location, motion and orientation of a referent. If two classifier predicates are used simultaneously, the signer can represent the spatial arrangement of both referents (Schembri, Jones and Burnham, 2001). This visual representation is new for learners with a spoken language background. Since there is a paucity of literature on second language (L2) sign language acquisition, there is no empirical evidence on the developmental stages that L2 learners go through in acquiring the devices to produce such visual representations. In this study, we followed 14 novel learners of Sign Language of the Netherlands (NGT) over a period of two years. The learners were asked to produce sign language descriptions of prompts containing various objects (e.g. cars, bicycles, trucks, human beings and animals) that could be depicted by a classifier predicate. Analyses show that after a year of instruction, the majority of learners are capable of producing scene descriptions featuring two classifier predicates to denote the spatial layout of the objects. The first classifier predicates appear in the data at an early stage, suggesting that the strategy of denoting an object with a meaningful handshape representing the object is not difficult to learn. Furthermore, the data show that learners initially struggle with the orientation of objects and handshape selection. This study is the first to systematically elicit classifier predicates from novel learners for an extended period of time. The results have important implications for the field of sign language pedagogy and teaching.
Traffic sign detection is an important task in traffic sign recognition systems. Chinese traffic signs have their unique features compared with traffic signs of other countries. Convolutional neural ...networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, we present a Chinese traffic sign detection algorithm based on a deep convolutional network. To achieve real-time Chinese traffic sign detection, we propose an end-to-end convolutional network inspired by YOLOv2. In view of the characteristics of traffic signs, we take the multiple 1 × 1 convolutional layers in intermediate layers of the network and decrease the convolutional layers in top layers to reduce the computational complexity. For effectively detecting small traffic signs, we divide the input images into dense grids to obtain finer feature maps. Moreover, we expand the Chinese traffic sign dataset (CTSD) and improve the marker information, which is available online. All experimental results evaluated according to our expanded CTSD and German Traffic Sign Detection Benchmark (GTSDB) indicate that the proposed method is the faster and more robust. The fastest detection speed achieved was 0.017 s per image.
The evaluation of sign language proficiency needs to be based on measures with well-established psychometric proprieties. To date, no valid and reliable test is available to assess Polish Sign ...Language (Polski Język Migowy, PJM) skills in deaf children. Hence, our aim with this study was to adapt the British Sign Language Receptive Skills Test (the first standardized test to determine sign language proficiency in children) into PJM, a less researched sign language. In this paper, we present the first steps in the adaptation process and highlight linguistic and cultural similarities and differences between the British Sign Language Receptive Skills Test and the PJM adaptation. We collected data from 20 deaf children who were native signers (age range: 6 to 12) and 30 deaf children who were late learners of PJM (age range: 6 to 13). Preliminary analyses showed that the PJM Receptive Skills Test has acceptable psychometric characteristics (item analysis, validity, reliability, and sensitivity to age). Our long-term goal with this work was to include younger children (age range: 3 to 6) and to standardize the PJM Receptive Skills Tests, so that it can be used in educational settings and in scientific research.
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