论文标题
多通道的多通道变压器
Multi-channel Transformers for Multi-articulatory Sign Language Translation
论文作者
论文摘要
符号语言使用多个异步信息渠道（铰接器），不仅是手和身体，而且脸部和身体通常会忽略计算方法。在本文中，我们解决了多通用手语翻译任务，并提出了一种新颖的多通道变压器体系结构。所提出的体系结构允许在变压器网络本身中建模不同的符号示意剂之间的间隔和内部上下文关系，同时还可以维护特定的渠道信息。我们在RWTH-Phoenix-Weather-2014T数据集上评估了我们的方法，并报告了竞争性翻译性能。重要的是，我们克服了对其他最先进方法的光泽注释的依赖，从而消除了未来对昂贵的策划数据集的需求。
Sign languages use multiple asynchronous information channels (articulators), not just the hands but also the face and body, which computational approaches often ignore. In this paper we tackle the multi-articulatory sign language translation task and propose a novel multi-channel transformer architecture. The proposed architecture allows both the inter and intra contextual relationships between different sign articulators to be modelled within the transformer network itself, while also maintaining channel specific information. We evaluate our approach on the RWTH-PHOENIX-Weather-2014T dataset and report competitive translation performance. Importantly, we overcome the reliance on gloss annotations which underpin other state-of-the-art approaches, thereby removing future need for expensive curated datasets.
