Some issues on Italian to LIS automatic translation. The case of train announcements
Authors: Carlo Geraci, Alessandro Mazzei, Marco Angster (CNRS, Università di Torino, Libera Università di Bolzano, 2014)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In this paper we present some linguistic issues of an automatic transla-tor from Italian to Italian Sign Language (LIS) and how we addressed them.

Introduction
Computational linguistic community showed a growing interest toward sign languages. Several projects of automatic translation into signed languages (SLs) recently started and avatar technology is becoming more and more popular as a tool for implementing automatic translation into SLs (Bangham et al. 2000, Zhao et al. 2000, Huenerfauth 2006, Morrissey et al. 2007, Su and Wu 2009). Current projects investigate relatively small domains in which avatars may perform decently, like post office announcements (Cox et al., 2002), weather forecasting (Verlinden et al., 2002), the jurisprudence of prayer (Almasoud and Al-Khalifa, 2011), driver’s license renewal (San-Segundo et al., 2012), and train announcements (e.g. Braffort et al. 2010, Ebling/Volk 2013). LIS4ALL is a project of automatic translation into LIS where we faced the domain of public transportation announcements. Specifically, we are developing a system of automatic translations of train station announcements from spoken Italian into LIS. The project is the prosecution of ATLAS, a project of automatic translation into LIS of weather forecasting (http://www.atlas. polito.it/index.php/en). In ATLAS two distinct approaches to automatic translation have been adopted, interlingua rule-based translation and statistical translation (Mazzei et al. 2013, Tiotto et al., 2010, Hutchins and Somer 1992). Both approaches have advantages and drawbacks in the specific context of automatic translation into SL. The statistical approach provides greater robustness while the symbolic approaches is more precise in the final results. A preliminary evaluation of the systems developed for ATLAS showed that both approaches have similar results. However, the symbolic approach we implemented produces the structure of the sentence in the target language. This information is used for the automatic allocation of the signs in the signing space for LIS (Mazzei et al. 2013), an aspect not yet implemented in current statistical approaches. LIS4ALL only uses the symbolic (rule-based) translation architecture to process the Italian input and generate the final LIS string. With respect to ATLAS, two main innovations characterize this project: new linguistic issues are addressed; the translation architecture is partially modified. As for the linguistic issues: we are enlarging the types of syntactic constructions covered by the avatar and we are increasing the electronic lexicon built for ATLAS (around 2350 signs) by adding new signs (around 120) specific to the railway domain. Indeed, this latter was one of the most challenging aspects of the project especially when the domain of train stations is addressed. Prima facie this issue would look like a special case of proper names, something that should be easily addressed by generating specific signs (basically one for every station). However, the solution is not as simple as it seems. Indeed, several problematic aspects are hidden when looking at the linguistic situation of names in LIS (and more generally in SL). As for the translation architecture, while in ATLAS a real interlingua translation with a deep parser and a FoL meaning representation were used, in LIS4ALL, we decided to employ a regular-expression-based analyzer that produces a simple (non recursive) filler/slot based semantic to parse the Italian input. This is so, because in the train announcement domain, input sentences have a large number of complex noun phrases with several prepositional phrases, resulting in a degraded parser performance (due to multiple attachment options). Moreover, the domain of application is extremely regular since the announcements are generated by predefined paths (RFI, 2011). The rest of the paper is organized as follows: Section 2 discusses the linguistic issues, Section 3 discusses the technical issues while Section 4 concludes the paper.

Conclusion
In this paper we considered two issues related to the development of an automatic translator from Italian to LIS in the railway domain. These are: 1) some syntactic mismatches between input and target languages; and 2) how to deal with lexical gaps due to unknown train station names. The first issue emerged in the creation of a parallel Italian-LIS corpus: the specificity of the domain allowed us to use a naive parser based on regular expressions, a semantic interpreter based on filler/slot semantics, a small CCG in generation. The second issue has been addressed by blending written text into a special “sign”. In the next future we plan to quantitatively evaluate our translator.