GPT-based Language Models meet Emojitaliano: A Preliminary Assessment Test between Automation and Creativity
Authors: Francesca Chiusaroli, Tiberio Uricchio, Johanna Monti, Maria Laura Pierucci, Federico Sangati (Università di Macerata, Università di Napoli L'Orientale, OIST Graduate University, 2023)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
Starting from the crowdsourcing experience of Pinocchio in Emojitaliano [1], the present paper intends to test Chat-GPT’s ability to take on the Emojitaliano grammar and dedicated glossary to verify and reapply the Emojitaliano rules in order to produce translations on its own. A test of re-translation of Pinocchio is presented here.

Introduction
Consisting today in over three thousand pictograms and symbols, and regularly updated by Unicode Consortium, the emoji international catalog contains signs for facial expressions (smileys) and for human gestures, portraits of people, plants and the animals, reproductions of food and objects for everyday activities and sports, symbols of travel and places. Whereas the visual content seems to provide an encyclopaedic catalog with a universal status, ideally able to signify language-independent meanings, the interpretation of emojis is, on the contrary, heavily arbitrary, subject to ambiguities and differences due to linguistic and cultural specificities [2]. Some efforts were made to develop an emoji based language that could be shared among different cultural peoples. The first notable project that made an effort of translating a classical novel (“Moby Dick” of Herman Melville), was the Emoji Dick project 1 by Fred Benenson (2010). Starting from the English version of the novel, each sentence was translated into an emoji version via crowdsourcing. Each of Moby Dick’s 6,438 sentences has been translated 3 times by different Amazon Mechanical Turk (MTurk) workers. The resulting emoji sentences were then chosen by voting by another set of workers, and the most popular version of each sentence was selected for inclusion in the book. The outcome is a wonderful but inconsistent translation of the same terms according to the wisdom of the crowd in good sense, but without any shared rules, structure or grammar, leading to the impossibility of recovering the original text or meaning. Another project was the translation of Lewis Carroll’s “Alice’s Adventures in Wonderland” by Joe Hale2 (2014). In this case, each word was directly translated into a corresponding emoji. Consistency was thus guaranteed as the same word was translated with the same emoji, introducing a de-facto lexicon. Nonetheless, no grammar structure is developed as the translation follows verbatim the original text and its English-based word order. In order to counteract the natural polysemy of emojis [3], Emojitaliano3 was created through a social community on Twitter (#scritturebrevi #emojitaliano), devoted to the experimental crowdsourcing construction of an international emoji code ‘emojilingua’ [4, 5]. The aim of the project includes linguistic simplification and the possibility of reproducing a text in emoji that will be comprehensible and readable in all languages of the world. For this reason, Emojitaliano consists in a unique project that provides a grammatical structure and a shared vocabulary. Emojitaliano is thus based on the assessment of conventional meanings, capable of guaranteeing the sharing of sense by means of intersemiotic translation [6]. The iconic property of emoji, together with the coded glossary and grammar, makes Emojitaliano a unique tool for communicative accessibility and for multilingual and language (L1 and L2) teaching. Born with the translation of Collodi’s Pinocchio, The Story of a Puppet4 [1], the structure and glossary of Emojitaliano have been later usefully reapplied for the translation of texts of different genres such as the technical declaratory prose of the Italian Constitution, the narrative prose of moral tales (i.e. The Wolf and the Lamb), Dante’s allegorical poetry of The Comedy, Giacomo Leopardi’s lyrical poem The infinite5. The process of such translation relied heavily on manual labor and human expertise, often time-consuming and subject to human limitations. With the rapid advancements in artificial intelligence, a new era has dawned upon the world of translation. Large Language Models (LLMs), such as BLOOM [7], GPT-3 [8], LLaMa-1 [9], have revolutionized the way we approach language translation. Recent chat interfaces enable an easy human interaction with them, that has led to a rapid and widespread adoption among the public, also due to the recent high performance closed models Chat-GPT and GPT-4, which remarkable are reported to be able to pass several human admission exams6. This preliminary assessment, thus, is about evaluating and establishing the utility of such models, even in the challenging application that is Emojitaliano, where figurative and idiomatic writing is needed, beyond the basic rules of the language.

Conclusion
Emojitaliano was born thanks to the free dedication and commitment of an enthusiast devoted Twitter social community, then also of student groups, willing to share the goal of building an emoji-based artificial language model, to be used as a communicative code across language barriers [5, 1]. The effort to adapt to the rules and to join the common glossary, as well as to expand it according to the common rules, was challenging as well as a hard task, but it was the only way to ensure an essential linguistic basis, by giving rise to a language, validated and practiced by a community of ‘speakers’. The intensive crowdsourcing experience made Emojitaliano a unique case among the (actually not many) examples of integral translations in emoji, which are mostly represented by intentionally non-systematic or solipsistic works. The regular expansion of the international emoji set by the Unicode Consortium constantly extends the range of choice by enriching the emoji-language with ‘emoji-neologisms’, as happens in every living natural language, but the core of the Emojitaliano glossary and grammar provides a settled authoritative translation method. Translating Pinocchio into Emojitaliano today would certainly involve new, and sometimes more relevant, pairings, synonymic pairs that do not exclude the previous ones; but the method remains fixed, because the syntax alone guarantees, through the instrument of translation, mutual understanding. Teaching Emojitaliano to GPT-4 (and the like) does not mean replacing a human translator with a machine, but rather is like having a tool to enhance human work to the maximum: automation ensures the speed, the iconic base of the emoji embeds and guides creativity, therefore setting limits against the arbitrary drift of individual subjective interpretation. Following our design, the year of work spent in the ‘human’ translation of the original 15 chapters of Pinocchio will be matched by a few minutes’ work in the translation of the entire work (35 chapters) by Chat-GPT, and in the translation of other works from any world’s language. Extreme speed is comfortable and convenient, but the results cannot be achieved without training: that is, by learning a “language” and its rules.