Impact of automatic segmentation on the quality, productivity and self-reported post-editing effort of intralingual subtitles

This paper describes the evaluation methodology followed to measure the impact of using a machine learning algorithm to automatically segment intralingual subtitles. The segmentation quality, productivity and self-reported post-editing effort achieved with such approach are shown to improve those obtained by the technique based in counting characters, mainly employed for automatic subtitle segmentation currently. The corpus used to train and test the proposed automated segmentation method is also described and shared with the community, in order to foster further research in this are

Speech technologies for the audiovisual and multimedia interaction environments

361 p

Mapping audiovisual translation investigations : research approaches and the role of technology

This article maps audiovisual translation research by analysing in a contrastive way the abstracts presented at three audiovisual translation conferences ten years ago and nowadays. The comparison deals with the audiovisual transfer modes and topics under discussion, and the approach taken by the authors in their abstracts. The article then shifts the focus to the role of technology in audiovisual translation research, as it is considered an element that is impacting and will continue to impact both research and practice in this field. Relevant research in audio-related, text-related and image-related technologies applied to audiovisual translation is summarised. The last section briefly discusses how technological tools can also help audiovisual translation professionals, users and researcher

The way out of the box

Synopsis: Cognitive aspects of the translation process have become central in Translation and Interpreting Studies in recent years, further establishing the field of Cognitive Translatology. Empirical and interdisciplinary studies investigating translation and interpreting processes promise a hitherto unprecedented predictive and explanatory power. This collection contains such studies which observe behaviour during translation and interpreting. The contributions cover a vast area and investigate behaviour during translation and interpreting – with a focus on training of future professionals, on language processing more generally, on the role of technology in the practice of translation and interpreting, on translation of multimodal media texts, on aspects of ergonomics and usability, on emotions, self-concept and psychological factors, and finally also on revision and post-editing. For the present publication, we selected a number of contributions presented at the Second International Congress on Translation, Interpreting and Cognition hosted by the Tra&Co Lab at the Johannes Gutenberg University of Mainz

Translation, interpreting, cognition

Cognitive aspects of the translation process have become central in Translation and Interpreting Studies in recent years, further establishing the field of Cognitive Translatology. Empirical and interdisciplinary studies investigating translation and interpreting processes promise a hitherto unprecedented predictive and explanatory power. This collection contains such studies which observe behaviour during translation and interpreting. The contributions cover a vast area and investigate behaviour during translation and interpreting – with a focus on training of future professionals, on language processing more generally, on the role of technology in the practice of translation and interpreting, on translation of multimodal media texts, on aspects of ergonomics and usability, on emotions, self-concept and psychological factors, and finally also on revision and post-editing. For the present publication, we selected a number of contributions presented at the Second International Congress on Translation, Interpreting and Cognition hosted by the Tra&Co Lab at the Johannes Gutenberg University of Mainz. Most of the papers in this volume are formulated in a particular constraint-based grammar framework, Head-driven Phrase Structure Grammar. The contributions investigate how the lexical and constructional aspects of this theory can be combined to provide an answer to this question across different linguistic sub-theories

Dodging the Data Bottleneck: Automatic Subtitling with Automatically Segmented ST Corpora

Speech translation for subtitling (SubST) is the task of automatically translating speech data into well-formed subtitles by inserting subtitle breaks compliant to specific displaying guidelines. Similar to speech translation (ST), model training requires parallel data comprising audio inputs paired with their textual translations. In SubST, however, the text has to be also annotated with subtitle breaks. So far, this requirement has represented a bottleneck for system development, as confirmed by the dearth of publicly available SubST corpora. To fill this gap, we propose a method to convert existing ST corpora into SubST resources without human intervention. We build a segmenter model that automatically segments texts into proper subtitles by exploiting audio and text in a multimodal fashion, achieving high segmentation quality in zero-shot conditions. Comparative experiments with SubST systems respectively trained on manual and automatic segmentations result in similar performance, showing the effectiveness of our approach

Dodging the Data Bottleneck: Automatic Subtitling with Automatically Segmented ST Corpora

Speech translation for subtitling (SubST) is the task of automatically translating speech data into well-formed subtitles by inserting subtitle breaks compliant to specific displaying guidelines. Similar to speech translation (ST), model training requires parallel data comprising audio inputs paired with their textual translations. In SubST, however, the text has to be also annotated with subtitle breaks. So far, this requirement has represented a bottleneck for system development, as confirmed by the dearth of publicly available SubST corpora. To fill this gap, we propose a method to convert existing ST corpora into SubST resources without human intervention. We build a segmenter model that automatically segments texts into proper subtitles by exploiting audio and text in a multimodal fashion, achieving high segmentation quality in zero-shot conditions. Comparative experiments with SubST systems respectively trained on manual and automatic segmentations result in similar performance, showing the effectiveness of our approach.Comment: Accepted to AACL 202

Improving the automatic segmentation of subtitles through conditional random field

[EN] Automatic segmentation of subtitles is a novel research field which has not been studied extensively to date. However, quality automatic subtitling is a real need for broadcasters which seek for automatic solutions given the demanding European audiovisual legislation. In this article, a method based on Conditional Random Field is presented to deal with the automatic subtitling segmentation. This is a continuation of a previous work in the field, which proposed a method based on Support Vector Machine classifier to generate possible candidates for breaks. For this study, two corpora in Basque and Spanish were used for experiments, and the performance of the current method was tested and compared with the previous solution and two rule-based systems through several evaluation metrics. Finally, an experiment with human evaluators was carried out with the aim of measuring the productivity gain in post-editing automatic subtitles generated with the new method presented.This work was partially supported by the project CoMUN-HaT - TIN2015-70924-C2-1-R (MINECO/FEDER).Alvarez, A.; Martínez-Hinarejos, C.; Arzelus, H.; Balenciaga, M.; Del Pozo, A. (2017). Improving the automatic segmentation of subtitles through conditional random field. Speech Communication. 88:83-95. https://doi.org/10.1016/j.specom.2017.01.010S83958

Easy Language Research

This volume presents new approaches in Easy Language research from three different perspectives: text perspective, user perspective and translation perspective. It explores the field of comprehensibility-enhanced varieties at different levels (Easy Language, Plain Language, Easy Language Plus). While all are possible solutions to foster communicative inclusion of people with disabilities, they have varying impacts with regard to their comprehensibility and acceptability. The papers in this volume provide insights into the current scientific activities and results of two research teams at the Universities of Hildesheim and Mainz and present innovative theoretical and empirical perspectives on Easy Language research. The approaches comprise studies on the cognitive processing of Easy Language, on Easy Language in multimodal and multicodal texts and different situational settings as well as translatological considerations on Easy Language translation and interpreting