论文标题
语言和签名语言中的签名语言之间的机器翻译
Machine Translation between Spoken Languages and Signed Languages Represented in SignWriting
论文作者
论文摘要
本文介绍了口语和签名语言之间的新型机器翻译（MT）系统的工作，其中签名语言在签名写作中表示，这是一种手语写作系统。我们的工作旨在解决当前MT系统中对签名语言的未开箱即用支持，并基于Signbank数据集，该数据集包含成对的口语文本和签名内容。我们介绍了新颖的方法来解析，分解，解码和评估签名写作，从而利用神经货物的想法。在双语设置（从美国手语到（美国）英语）中，我们的方法实现了30多个BLEU，而在两个多语言设置中 - 在口语语言和签名语言之间的两个方向上都可以译用20多个BLEU。我们发现，用于改善口头翻译的常见MT技术类似地影响了手语翻译的性能。这些发现证明了我们使用中间文本表示签名语言，以将其包括在自然语言处理研究中。
This paper presents work on novel machine translation (MT) systems between spoken and signed languages, where signed languages are represented in SignWriting, a sign language writing system. Our work seeks to address the lack of out-of-the-box support for signed languages in current MT systems and is based on the SignBank dataset, which contains pairs of spoken language text and SignWriting content. We introduce novel methods to parse, factorize, decode, and evaluate SignWriting, leveraging ideas from neural factored MT. In a bilingual setup--translating from American Sign Language to (American) English--our method achieves over 30 BLEU, while in two multilingual setups--translating in both directions between spoken languages and signed languages--we achieve over 20 BLEU. We find that common MT techniques used to improve spoken language translation similarly affect the performance of sign language translation. These findings validate our use of an intermediate text representation for signed languages to include them in natural language processing research.
