5.1 Introduction

One of the challenges in the study of sign language linguistics is the collection and representation of linguistic data. In computational linguistics, this problem is even more crippling, since data are the basis of any computational approach to a subject.

There is an increasing interest both in society and the scientific community in sign languages, and corpora have been created for many different sign languages and with varying schemes of annotation. However, most corpora are video-based, which is equivalent to the hypothetical case of corpora of oral languages being mostly based on audio recordings.

Recordings of real utterances, both of oral or signed languages, are difficult to process computationally, whether it is for searching or managing the data, or for linguistically analyzing it and finding its structure and meaning. Video is especially difficult, since the human visual system is highly sophisticated, and emulating its processes with artificial intelligence is not a solved problem yet.

In oral languages, writing poses a useful alternative to recordings, and is indeed (and maybe to a fault) the basis on which computational linguistics have been built. However, there does not exist an equivalent in signed languages. There is not a widely accepted written form for these languages, even less a literature or a corpus of real world linguistic data that can be exploited.

There exist some candidates for this, the most promising being SignWriting. SignWriting is a system that can act as a written form of sign language, or at least as a transcription system for it. It is iconic and very in-line with the visual nature of sign languages, so it is easy to understand and accept by native signers. The problem is that it is not as easy to use in the digital world, not being formed by linear strings of characters that can be quickly input with a keyboard and consumed by the many tools developed by the computational linguistics community.

We present an early-stage project for developing tools and resources that aim to facilitate the effective use of SignWriting in computers. With these tools, input of SignWriting can be as quick as writing it on paper, and no further processing by the user is necessary. Other tools will also use this input to generate related output, such as a textual description of the signer’s actions or an animated avatar, which means that SignWriting will be useful as a digital representation of sign language even for users not familiar with it. This can help in the teaching of sign language, by facilitating the use of this language in computers, and also increase accessibility and inclusion of the Deaf community in the digital world.

In the next section, we give a brief overview of the problems of sign language notation, and quickly explain SignWriting and computer vision, the artificial intelligence tool to be used for its processing. Section 5.3 explicates the architecture of the project and its different components, and in Section 5.4 some conclusions are drawn.