Stylometry in Computer-Assisted Translation: Experiments on the Babylonian Talmud
Authors: Emiliano Giovannetti, Davide Albanesi, Andrea Bellandi, David Dattilo, Felice Dell'Orletta (CNR-ILC, Progetto Traduzione Talmud Babilonese S.c.a r.l., 2017)
Topic: Lexical and Semantic Resources and Analysis

Abstract
The purpose of this research is to experiment the application of stylometric techniques in the area of Computer-Assisted Translation to reduce the revision effort in the context of a collaborative, large scale translation project. The obtained results show a correlation between the editing extent and the compliance to some specific linguistic features, suggesting that supporting translators in writing translations following a desired style may actually reduce the number of following necessary interventions (and, consequently, save time) by revisors, editors and curators.

Introduction
The Progetto Traduzione Talmud Babilonese (PTTB) is a research and education project carrying out the digitized Italian translation of the Babylonian Talmud (BT), a fundamental book of the Jewish tradition, covering every aspect of human knowledge: law, science, philosophy, religion and even aspects of everyday life. The translation of the Talmud has been assigned to more than 50 scholars comprising expert translators, trainee translators, instructors, editors and curators. The translated text is accompanied by the explanations and comments on specific words and subjects, and also by illustrative sheets for the various scientific, historical and linguistic topics addressed inside the Talmudic discussions. However, the Project objectives include more than the translation of the Talmud: the whole work has been set up to be completely digital. Everything, from the very first activities of assigning users to the translation of specific chapters to supporting in the definition of the final printing layout, revolves around Traduco, a collaborative web-based Computer-Assisted Translation (CAT) tool developed within the Project. Today, many CAT tools, both commercial and freely distributed, are already available, but they have been designed for the translation of technical manuals or domain-specific texts (legislative, medical) with the main purpose of speeding up the translation process. The BT is a very complex text in many ways: its content, the different, ancient, languages it is composed of (though mainly Babylonian Aramaic and Mishnaic Hebrew), and the history of its composition over the centuries. For these reasons, the approach we adopted for the development of Traduco had to take into account the needs of translators working on a text with very particular interpretative issues. Traduco allows a user to distinguish the literal part of the translation (in bold, see Fig.fig:lifeCycle) from explicative additions, included by translators to make the most difficult passages clearer to readers. Indeed, a full understanding of this kind of texts requires a translation to be enriched with comments, notes, and glossary entries. Furthermore, due to the complexity of the inner structure of the BT, Traduco allows users to split autonomously their translations into ``strings'' (representing, typically, a sentence, see Fig.fig:lifeCycle), gathered into ``logical units'' . Finally, Traduco provides a collaborative and training environment allowing a translator to instantly consult translations done by others, when portions of text (and sometimes even a single word) are difficult to interpret and translate. For a comprehensive description of how Traduco works refer to AUTHOR. The size and complexity of the text and the need to produce a printed version of the BT translation, required a team of users composed of translators, revisors, editors, curators and supervisors. The whole translation workflow can be described by following the ``life-cycle'' of each string (Fig.fig:lifeCycle). It all starts as soon as the coordinator of the translation assigns a chapter to a specific translator: the first phase of the work, the translation, begins. The translation is carried out by scholars having two distinct profiles: expert translators, working autonomously, and trainee translators, these latter being constantly supported by instructors monitoring online their work and providing face-to-face lectures. Once the translation of a specific chapter is concluded, the revision phase starts. Revisors are chosen among the most expert scholars involved in the Project and their main task is to verify if translators have understood correctly the meaning of each string. They also have to check if the domain terms (if present) have been appropriately annotated and explained in the relative glossary entry. After the content has been revised, the editing starts. In this phase, a formal and linguistic control of the translation is carried out, where the editors ensure that the translated strings are syntactically and orthographically correct. Contextually, each string can be enriched, if needed to help in the understanding of the text, with pictures and tables. The last phase is the curatorship, during which one more general control of the translation is done before proceeding with the final exporting and printing of the volume. As we showed in a previous work AUTHOR, the introduction of Natural Language Processing techniques in CAT tools can bring concrete advantages to the translation work and pave the way to innovative research in the area of NLP for Digital Humanities. One way to ease the translation of a text as the BT is to assist translators in writing, in the first place, good translations requiring as few corrections as possible by revisors, editors and curators. In other words, we want to find a way of alerting a user about to submit a new translation by highlighting specific characteristics of the sentence that may further require a revision and, thus, slow down the overall translation process. To do that, we chose to experiment the application of stylometric measures to Italian translations. The assumption we would like to prove is that translations being more compliant to the style of revisors will actually require less revisions. If that will be demonstrated, we may develop a strategy to alert translators of potential ``unfit'' translations and suggest a way to improve them in order to minimize the following editing for revision, editing, and curatorship.

Conclusion
The experiment described in this paper proves that the application of NLP to CAT contexts can open new research perspectives and, more importantly, may be of concrete help in real usage translation scenarios. The proposed methodology can be applied, in principle, to any translation project in which a revision phase is a part of the whole translation workflow and where an history of the edits is maintained. The same analysis could be performed on different languages depending solely on the availability of the suitable NLP tools. Some of the NLP techniques adopted for the stylometric analysis of Italian may also be adapted to the processing of Mishnaic Hebrew and Aramaic (the main source languages). The automatic linguistic analysis of Mishnaic Hebrew, for example, is being experimented AUTHOR. However, an analysis of the style (or complexity) of the source text, though interesting in a historical text analysis perspective, would be pointless in the specific context of revision support in computer-assisted translation. The correlation we found between the revision measures and some linguistic features (some of which are actually used as indicators of linguistic complexity) is the first step towards the design of a technique aimed at providing users a way of writing translations less prone to revisions. In this way, the whole translation workflow would benefit from a reduced time in the revision, editing and curatorship phases. Once the approach will be defined, the relative software will be implemented as a new component of Traduco. Moreover, the possibility of suggesting a way of writing ``better'' translations (at least wrt revisor's style) will be exploited in the education of trainee translators.