论文标题
语言中语音参数的分类
Classification of Phonological Parameters in Sign Languages
论文作者
论文摘要
签名人组成手语音素，通过结合语音参数（例如握手，方向，位置，运动和非手动特征）来启用通信。语言研究经常将标志分解为其组成部分以研究标志语言，并且经常将大量精力投入到视频的注释中。在这项工作中，我们展示了如何使用单个模型来识别符号语言中的单个语音参数，目的是协助语言注释或描述标志识别模型的标志。我们使用丹麦语手语数据集``dansk tegnsprog''使用姿势估计模型生成多个数据集，然后将其用于训练多标签快速R-CNN模型以支持多标签建模。此外，我们表明，生成数据中的方向和位置语音参数之间存在显着的共同依赖性，并且我们将这种共依赖性纳入了模型中，以实现更好的性能。
Signers compose sign language phonemes that enable communication by combining phonological parameters such as handshape, orientation, location, movement, and non-manual features. Linguistic research often breaks down signs into their constituent parts to study sign languages and often a lot of effort is invested into the annotation of the videos. In this work we show how a single model can be used to recognise the individual phonological parameters within sign languages with the aim of either to assist linguistic annotations or to describe the signs for the sign recognition models. We use Danish Sign Language data set `Ordbog over Dansk Tegnsprog' to generate multiple data sets using pose estimation model, which are then used for training the multi-label Fast R-CNN model to support multi-label modelling. Moreover, we show that there is a significant co-dependence between the orientation and location phonological parameters in the generated data and we incorporate this co-dependence in the model to achieve better performance.
