Vantaggi e limiti dell'integrazione tra sistemi di traduzione assistita e sistemi di traduzione automatica

Computer-assisted translation (or computer-aided translation or CAT) is a form of language translation in which a human translator uses computer software in order to facilitate the translation process. Machine translation (MT) is the automated process by which a computerized system produces a translated text or speech from one natural language to another. Both of them are leading and promising technologies in the translation industry; it therefore seems important that translation students and professional translators become familiar with this relatively new types of technology. Whether used together, not only might these two different types of systems reduce translation time, but also lead to a further improvement in the field of translation technologies. The dissertation consists of four chapters. The first one surveys the chronological development of MT and CAT tools, the emergence of pre-editing, post-editing and controlled language and the very last frontiers in this sector. The second one provide a general overview on the four main CAT tools that are used nowadays and tested hereto. The third chapter is dedicated to the experimentations that have been conducted in order to analyze and evaluate the performance of the four integrated systems that are the core subject of this dissertation. Finally, the fourth chapter deals with the issue of terminological equivalence in interlinguistic translation. The purpose of this dissertation is not to provide an objective and definitive solution to the complex issues that arise at any time in the field of translation technologies, this aim being well away from being achieved, but to supply information about the limits and potentiality that are typical of those instruments which are now essential to any professional translator.

Augmented Audiovisual Translation: the Perks and Perils of the Implementation of Artificial Intelligence in Subtitling and Dubbing

This thesis examines the state of audiovisual translation (AVT) in the aftermath of the COVID-19 emergency, highlighting new trends with regards to the implementation of AI technologies as well as their strengths, constraints, and ethical implications. It starts with an overview of the current AVT landscape, focusing on future projections about its evolution and its critical aspects such as the worsening working conditions lamented by AVT professionals – especially freelancers – in recent years and how they might be affected by the advent of AI technologies in the industry. The second chapter delves into the history and development of three AI technologies which are used in combination with neural machine translation in automatic AVT tools: automatic speech recognition, speech synthesis and deepfakes (voice cloning and visual deepfakes for lip syncing), including real examples of start-up companies that utilize them – or are planning to do so – to localize audiovisual content automatically or semi-automatically. The third chapter explores the many ethical concerns around these innovative technologies, which extend far beyond the field of translation; at the same time, it attempts to revindicate their potential to bring about immense progress in terms of accessibility and international cooperation, provided that their use is properly regulated. Lastly, the fourth chapter describes two experiments, testing the efficacy of the currently available tools for automatic subtitling and automatic dubbing respectively, in order to take a closer look at their perks and limitations compared to more traditional approaches. This analysis aims to help discerning legitimate concerns from unfounded speculations with regards to the AI technologies which are entering the field of AVT; the intention behind it is to humbly suggest a constructive and optimistic view of the technological transformations that appear to be underway, whilst also acknowledging their potential risks.

The future of dubbing: an overview of the new technologies

Throughout the years, technology has had an undeniable impact on the AVT field. It has revolutionized the way audiovisual content is consumed by allowing audiences to easily access it at any time and on any device. Especially after the introduction of OTT streaming platforms such as Netflix, Amazon Prime Video, Disney+, Apple TV+, and HBO Max, which offer a vast catalog of national and international products, the consumption of audiovisual products has been on a constant rise and, consequently, the demand for localized content too. In turn, the AVT industry resorts to new technologies and practices to handle the ever-growing workload and the faster turnaround times. Due to the numerous implications that it has on the industry, technological advancement can be considered an area of research of particular interest for the AVT studies. However, in the case of dubbing, research and discussion regarding the topic is lagging behind because of the more limited impact that technology has had on the very conservative dubbing industry. Therefore, the aim of the dissertation is to offer an overview of some of the latest technological innovations and practices that have already been implemented (i.e. cloud dubbing and DeepDub technology) or that are still under development and research (i.e. automatic speech recognition and respeaking, machine translation and post-editing, audio-based and visual-based dubbing techniques, text-based editing of talking-head videos, and automatic dubbing), and respectively discuss their reception by the industry professionals, and make assumptions about their future implementation in the dubbing field.