Babel - Online First

After more than seventy years, when Kahlil Gibran’s 1923 masterpiece The Prophet had circulated freely in Egypt, censorship authorities banned the book in 1999 and 2011. This article explores the sociopolitical context surrounding the censorship of The Prophet and its Arabic translations, with a particular focus on the power play between censors and different agents and the strategies employed by the latter to revoke the ban on the book. The extent and intensity of power intervention speak to this case study’s significance. Qualitative analysis of English and Arabic press material is utilized to gain insights into the censors’ reports and the responses of different sociopolitical agents. This is paired with compiling and analyzing a dataset of bibliographical information on the editions of The Prophet’s Arabic translations published in Egypt between 1999 and 2022. The findings point to a decentralized system of censorship exercised by several ministries and religious institutions with competing interests. It is argued that the survival of The Prophet in the face of multiple bans can be attributed to shifting sociopolitical conditions, discordant politics of powerful agents, and international pressure.

This article discusses the challenges that the rendering of the pragmatic implications of texts into a target language posed for human translators and, by extension, for automated translation. It starts by discussing the importance of pragmatics, focusing on two concepts that have received much attention on the part of pragmaticians as well as translation scholars, namely implicatures and politeness. It moves to on to present some of the most notable publications on the interface between pragmatics and machine translation. These illustrate that the interest in the pragmatic value of language has not succeeded in advancing the integration of pragmatics into automated translation. Drawing on Kesckes and House, the last section discusses two concepts to be considered regarding the role of pragmatics in intercultural mediation.

This study examines the performance of the neural machine translation system DeepL in translating Shakespeare’s plays Coriolanus and The Merchant of Venice. The aim here is to explore the strengths and limitations of an AI-based English-Chinese translation of literary texts. Adopting a corpus-based approach, the study investigates the accuracy and fluency rates, the linguistic features, and the use of various methods of translation in the Chinese translations of Shakespeare’s plays conducted via DeepL. It compares these to the translations by Liang Shiqiu, a well-known Chinese translator. The study finds that DeepL performs well in translating these works, with an accuracy and fluency rate of above 80% in sampled texts, showing the potential of the use of neural machine translation in translating literary texts across distant languages. Our research further reveals that the DeepL translations exhibit a certain degree of creativity in their use of translation methods such as addition, explicitation, conversion and shift of perspective, and in the use of Chinese sentence-final modal particles, as well as Chinese modal verbs. On the other hand, the system appears to be limited in that a certain amount of translation errors are present, including literal translations.

Technological advancement has brought changes to many professions across the world. Furthermore, it has triggered a discussion about ethical issues. Machine Translation (MT) or Computer-Aided Translation (CAT) has vastly increased work efficiency and technology-related ethical issues are gaining academic attention these days. However, the discussion of ethical issues for literary translation against the backdrop of Artificial Intelligence (AI) is limited. After a quick review of the stages of MT, this paper will delve into literary translation’s emerging ethical issues, for example, the literary translator’s professional identity and copyright. Copyright ethics is an indispensable part of AI-enabled literary translation since training data and participatory NMT involve copyright issues. This study revealed that technological advancement will facilitate literary translation. However, no direct evidence exists that machine translation will replace human translators. Given the new working mode of “multi-players” or participatory translation, ethical issues arising from the human and machine interaction merit further academic inquiry.

This paper revisits Roman Jakobson’s literaturnost within the framework of modern poetics and in light of the challenge posed by artificial intelligence to human literary translation. It is argued that literary translation is, in essence, more of a project of code transposition and meaning generation than of message transmission. Furthermore, it is noted that although algorithms can process certain literary devices, they are currently unable to process the polysystemic relations that constitute an artwork’s literaturnost. Consequently, it is emphasized that meaning transferal, meaning generation, and the revolt against meaning will continue to pose barriers for future machine translation even in the long term.