Recycling texts: human evaluation of example-based machine translation subtitles for DVD

This project focuses on translation reusability in audiovisual contexts. Specifically, the project seeks to establish (1) whether target language subtitles produced by an EBMT system are considered intelligible and acceptable by viewers of movies on DVD, and (2)whether a relationship exists between the ‘profiles’ of corpora used to train an EBMT system, on the one hand, and viewers’ judgements of the intelligibility and acceptability of the subtitles produced by the system, on the other. The impact of other factors, namely: whether movie-viewing subjects have knowledge of the soundtrack language; subjects’ linguistic background; and subjects’ prior knowledge of the (Harry Potter) movie clips viewed; is also investigated. Corpus profiling is based on measurements (partly using corpus-analysis tools) of three characteristics of the corpora used to train the EBMT system: the number of source language repetitions they contain; the size of the corpus; and the homogeneity of the corpus (independent variables). As a quality control measure in this prospective profiling phase, we also elicit human judgements (through a combined questionnaire and interview) on the quality of the corpus data and on the reusability in new contexts of the TL subtitles. The intelligibility and acceptability of EBMT-produced subtitles (dependent variables) are, in turn, established through end-user evaluation sessions. In these sessions 44 native German-speaking subjects view short movie clips containing EBMT-generated German subtitles, and following each clip answer questions (again, through a combined questionnaire and interview) relating to the quality characteristics mentioned above. The findings of the study suggest that an increase in corpus size along with a concomitant increase in the number of source language repetitions and a decrease in corpus homogeneity, improves the readability of the EBMT-generated subtitles. It does not, however, have a significant effect on the comprehensibility, style or wellformedness of the EBMT-generated subtitles. Increasing corpus size and SL repetitions also results in a higher number of alternative TL translations in the corpus that are deemed acceptable by evaluators in the corpus profiling phase. The research also finds that subjects are more critical of subtitles when they do not understand the soundtrack language, while subjects’ linguistic background does not have a significant effect on their judgements of the quality of EBMT-generated subtitles. Prior knowledge of the Harry Potter genre, on the other hand, appears to have an effect on how viewing subjects rate the severity of observed errors in the subtitles, and on how they rate the style of subtitles, although this effect is training corpus-dependent. The introduction of repeated subtitles did not reduce the intelligibility or acceptability of the subtitles. Overall, the findings indicate that the subtitles deemed the most acceptable when evaluated in a non-AVT environment (albeit one in which rich contextual information was available) were the same as the subtitles deemed the most acceptable in an AVT environment, although richer data were gathered from the AVT environment

A method of rapid curriculum development for foreign language teaching

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Understanding video through the lens of language

The increasing abundance of video data online necessitates the development of systems capable of understanding such content. However, building these systems poses significant challenges, including the absence of scalable and robust supervision signals, computational complexity, and multimodal modelling. To address these issues, this thesis explores the role of language as a complementary learning signal for video, drawing inspiration from the success of self-supervised Large Language Models (LLMs) and image-language models. First, joint video-language representations are examined under the text-to-video retrieval task. This includes the study of pre-extracted multimodal features, the influence of contextual information, joint end-to-end learning of both image and video representations, and various frame aggregation methods for long-form videos. In doing so, state-of-the-art performance is achieved across a range of established video-text benchmarks. Second, this work explores the automatic generation of audio description (AD) – narrations describing the visual happenings in a video, for the benefit of visually impaired audiences. An LLM, prompted with multimodal information, including past predictions, and pretrained with partial data sources, is employed for the task. In the process, substantial advancements are achieved in the following areas: efficient speech transcription, long-form visual storytelling, referencing character names, and AD time-point prediction. Finally, audiovisual behaviour recognition is applied to the field of wildlife conservation and ethology. The approach is used to analyse vast video archives of wild primates, revealing insights into individual and group behaviour variations, with the potential for monitoring the effects of human pressures on animal habitats

Tigrigna language spellchecker and correction system for mobile phone devices

This paper presents on the implementation of spellchecker and corrector system in mobile phone devices, such as a smartphone for the low-resourced Tigrigna language. Designing and developing a spell checking for Tigrigna language is a challenging task. Tigrigna script has more than 32 base letters with seven vowels each. Every first letter has six suffixes. Word formation in Tigrigna depends mainly on root-and-pattern morphology and exhibits prefixes, suffixes, and infixes. A few project have been done on Tigrigna spellchecker on desktop application and the nature of Ethiopic characters. However, in this work we have proposed a systems modeling for Tigrigna language spellchecker, detecting and correction: a corpus of 430,379 Tigrigna words has been used. To indication the validity of the spellchecker and corrector model and algorithm designed, a prototype is developed. The experiment is tested and accuracy of the prototype for Tigrigna spellchecker and correction system for mobile phone devices achieved 92%. This experiment result shows clearly that the system model is efficient in spellchecking and correcting relevant suggested correct words and reduces the misspelled input words for writing Tigrigna words on mobile phone devices

“Did you know that David Beckham speaks nine languages?”:AI-supported production process for enhanced personalization of audio-visual content

The introduction of artificial intelligence (AI) into the media production process has contributed to the automation of selected tasks and stronger hybridization of man and machine in the process; however, the AI-supported production process has expanded from the traditional, three-stage model by a new phase of consumer evaluation and feedback collection, analysis, and application. This has opened a way for far-reaching content personalization and thus offers a new type of media experience. Powering the production process with a constant stream of consumer data has also affected the process itself and changed its nature from linear to cyclical

Speech technologies for the audiovisual and multimedia interaction environments

361 p

Quality in subtitling: theory and professional reality

The issue of quality is of great importance in translation studies and, although some studies have been conducted in the field of subtitling, most discussions have been limited to aspects such as how to become a good subtitler and how to produce quality subtitles. Little research has been carried out to investigate other potential factors that may influence the quality of subtitling output in practice. In recent years, some subtitling courses at postgraduate level have attempted to bridge the gap between academia and industry, not only by incorporating the teaching of linguistic and technical skills into the curriculum but also by informing students about ethics, working conditions, market competition, and other relevant professional issues. This instruction is intended to prepare them for promising careers in the subtitling industry, where a progressively deteriorating trend has been observed by some professional subtitlers. The main aim and objective of this study is to explore both theoretical and practical aspects of subtitling quality. The study aspires to call attention to the factors influencing the quality of subtitles and also to provide suggestions to improve the state of affairs within the subtitling industry in terms of quality. In order to examine the potential factors that influence the perception of subtitling quality, particularly in the professional context, two rounds of online surveys were conducted to establish the working conditions of subtitlers. Despite the fact that the participants in the first survey were based in thirty-nine different countries, the data collected is more representative of the situation in Europe, where subtitling is a relatively mature industry compared to other parts of the world. The second survey targeted subtitlers working with the Chinese language in an attempt to study the burgeoning Chinese audiovisual market. This thesis provides a systematic analysis of the numerous parameters that have an impact on the quality of subtitling, both in theory and in professional reality, and offers a detailed insight into the working environment of subtitlers. At the same time, it endeavours to draw attention to the need to ensure decent working conditions in the industry. The general findings are discussed in terms of their implications for the development of the profession as well as for subtitler training and education.Open Acces