Sign language recognition with transformer networks

Sign languages are complex languages. Research into them is ongoing, supported by large video corpora of which only small parts are annotated. Sign language recognition can be used to speed up the annotation process of these corpora, in order to aid research into sign languages and sign language recognition. Previous research has approached sign language recognition in various ways, using feature extraction techniques or end-to-end deep learning. In this work, we apply a combination of feature extraction using OpenPose for human keypoint estimation and end-to-end feature learning with Convolutional Neural Networks. The proven multi-head attention mechanism used in transformers is applied to recognize isolated signs in the Flemish Sign Language corpus. Our proposed method significantly outperforms the previous state of the art of sign language recognition on the Flemish Sign Language corpus: we obtain an accuracy of 74.7% on a vocabulary of 100 classes. Our results will be implemented as a suggestion system for sign language corpus annotation

What is corpus linguistics? What the data says

Stubbs (2006), in his state of the art overview, draws attention to the frequent reticence or vagueness of corpus analysts in discussing their operational methods within a scientific context, (a context addressed in detail in Partington forthcoming). This lack of clarity in discussing the methodological framework employed is, perhaps, most surprising given the way in which corpus linguistics situates itself within a scientific frame, and lays such claims to a scientific nature. This brief paper, then, addresses the question posed in its title, namely, “What is corpus linguistics?” – is it a discipline, a methodology, a paradigm or none or all of these? – but does not attempt to offer any definitive answers. Rather, the aim is to present the reader with a number of observations on how corpus linguistics has been construed in its own literature and then to leave the question open, in the hope of stimulating further discussion. The study takes the specific term corpus linguistics and looks at how it is defined and described both explicitly and implicitly in a variety of relevant sources