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24 results for “subtitling”
DEEPICE Stories Videos series - Insight into Ice & Climate - Videos with English subtitles
<p><em>DEEPICE Stories – Insights into Ice & Climate </em>is a series of 15 videos<em> </em>created in collaboration with the 15 PhD students of the European research project <a href="https://deepice.cnrs.fr/">DEEPICE</a>. These 3-minute educational video clips give an overview of scientific research on ice cores. <a href="https://deepice.cnrs.fr">https://deepice.cnrs.fr</a></p> <p> </p> <p><u>Credits</u></p> <p>Writing & presentation: Geunwoo Lee, Hanne <span>Notø</span>, Eirini <span>Malegiannaki</span>, Piers Larkman, Miguel Angel Sanchez Moreno, Lison Soussaintjean, Florian Painer, Niklas Kappelt, Lisa Ardoin, Inès Ollivier, Romilly Harris Stuart, Fyntan Shaw, Qinggang Gao, Ailsa Chung, Daniel Gunning</p> <p>Coordination : Marie Kazeroni (LSCE-CNRS)</p> <p>Direction: Dorothée Adam-Mazard (Inuaprod) & Marie Kazeroni (LSCE-CNRS)</p> <p>Editing: Thomas d’Aram</p> <p>Motion Design: Pauline Fuchs</p> <p>Co-production: DEEPICE & Inuaprod</p>
Pivot subtitling of Korean dramas on Netflix Türkiye between 2015 and 2023
<p>This dataset complements the research article <em>Pivot Subtitling on Netflix: the Case of Squid Game </em>(Dallı, 2024) and provides comprehensive information on Korean dramas and their subtitlers on Netflix Türkiye from 2015 to 2023. It also includes an analysis report derived from the raw findings. The data was manually compiled in January 2024.</p> <p>The dataset comprises the following files:</p> <ol> <li><strong>turkish-subtitlers-of-korean-content-on-netflix:</strong> This file provides raw data on Korean dramas, including Netflix release date, title, episode count, assigned subtitlers, number of subtitlers involved, and translation methods (subtitling or dubbing).</li> <li><strong>pivot-subtitling-on-netflix_the-case-of-squid-game:</strong> This R Markdown file offers an analysis report examining the yearly trends of Korean dramas released on Netflix Türkiye and the average number of Turkish subtitlers per drama.</li> </ol> <p>This dataset is designed to help understand trends in the release of Korean dramas on Netflix, with a particular focus on Turkish subtitlers. It is valuable for researchers, practitioners, and industry stakeholders interested in Korean content and pivot subtitling, providing insights into the distribution dynamics and subtitling trends in Korean media.</p> <p>Keywords: pivot subtitling, pivot templates, pivot audiovisual translation, indirect translation, Korean dramas, Turkish subtitlers, <em>Squid Game</em>.</p> <p>Dallı, H. (2024). Pivot Subtitling on Netflix: the Case of Squid Game. <em>Journal of Audiovisual Translation</em>, <em>7</em>(1).</p>
Northern Sami YleAreena Subtitle Corpus
<p>A corpus of Northern Sami language subtitle sentences collected from YLE Sápmi broadcasts (March 31st 2021 - November 15th 2024).</p> <p> </p> <p>The corpus includes:<br>- Full sentences, cleaned and collected from the subtitles<br>- Sentence IDs<br>- Complete source metadata</p> <p><br><span><span>=== Basic Statistics === </span><br>Total Words: 7776 <br>Unique Words: 3033 <br>Total Sentences: 835 <br>Average Sentence Length: 9.31 words <br>Median Sentence Length: 8.0 words <br>Type-Token Ratio: 0.39 <br>Sentence Length Std Dev: 5.62 <br><br>=== Top 10 Most Frequent Words === <br>lea: 239 <br>ja: 227 <br>dat: 202 <br>leat: 186 <br>ahte: 166 <br>mun: 124 <br>go: 105 <br>ii: 71 <br>dan: 70 <br>mii: 69<br><br></span></p>
Survey on Turkish Subtitlers of Korean Content
<p>This dataset contains anonymized survey responses and descriptive statistics related to the article <em>The state of pivot subtitling: a survey on Turkish subtitlers of Korean content</em>. The online survey was conducted on <a href="https://www.surveymonkey.com/">SurveyMonkey</a> between September 2022 and April 2023. The dataset includes responses gathered from Turkish subtitlers, primarily focusing on the concept of pivot subtitling.</p> <p>The dataset comprises the following files:</p> <ol> <li><strong>Anonymized Survey Responses in Turkish:</strong> This file contains raw anonymized responses to the survey questions collected from participants in Turkish.</li> <li><strong>Analysis Report in Turkish:</strong> This file presents descriptive statistics derived from the survey responses in the original language Turkish.</li> <li><strong>Analysis Report in English:</strong> This file provides translated versions of the survey data analysis report.</li> </ol> <p>The dataset is intended to understand the working conditions of Turkish pivot subtitlers, focusing on Korean content. Researchers, practitioners, and other industry stakeholders interested in pivot subtitling may find this dataset valuable for understanding the dynamics of pivot subtitling.</p> <p>Keywords: pivot subtitling, pivot templates, pivot audiovisual translation, indirect translation, Korean dramas, Turkish subtitlers, survey study, questionnaire, quality assurance.</p> <p>Citation (APA 7th): Dallı, H., & Sung, S. (2024). The state of pivot subtitling: a survey on Turkish subtitlers of Korean content. FORUM, 22 (1).</p>
DEEPICE Stories Videos series - Insight into Ice & Climate - Videos with French subtitles
<p><em>DEEPICE Stories – Insights into Ice & Climate </em>is a series of 15 videos<em> </em>created in collaboration with the 15 PhD students of the European research project <a href="https://deepice.cnrs.fr/">DEEPICE</a>. These 3-minute educational video clips give an overview of scientific research on ice cores. <a href="https://deepice.cnrs.fr">https://deepice.cnrs.fr</a></p> <p><u>Credits</u></p> <p>Writing & presentation: Geunwoo Lee, Hanne Notø, Eirini Malegiannaki, Piers Larkman, Miguel Angel Sanchez Moreno, Lison Soussaintjean, Florian Painer, Niklas Kappelt, Lisa Ardoin, Inès Ollivier, Romilly Harris Stuart, Fyntan Shaw, Qinggang Gao, Ailsa Chung, Daniel Gunning</p> <p>Coordination : Marie Kazeroni (LSCE-CNRS)</p> <p>Direction: Dorothée Adam-Mazard (Inuaprod) & Marie Kazeroni (LSCE-CNRS)</p> <p>Editing: Thomas d’Aram</p> <p>Motion Design: Pauline Fuchs</p> <p>Co-production: DEEPICE & Inuaprod</p> <p>___________________________________________________________________________________________________________________</p> <p><em><span>DEEPICE Stories - Insights into Ice & Climate </span></em><span>est une série de 15 vidéos créées en collaboration avec les 15 doctorants du projet de recherche européen <a href="https://deepice.cnrs.fr/">DEEPICE</a>. Ces capsules éducatives de 3 minutes donnent un aperçu de la recherche scientifique sur les carottes de glace. <a href="https://deepice.cnrs.fr">https://deepice.cnrs.fr</a></span></p> <p>Crédits</p> <p><span><span>Ecriture et présentation : Geunwoo Lee, Hanne Notø, Eirini Malegiannaki, Piers Larkman, Miguel Angel Sanchez Moreno, Lison Soussaintjean, Florian Painer, Niklas Kappelt, Lisa Ardoin, Inès Ollivier, Romilly Harris Stuart, Fyntan Shaw, Qinggang Gao, Ailsa Chung, Daniel Gunning<br></span></span></p> <p><span><span>Coordination : Marie Kazeroni (LSCE-CNRS)</span></span></p> <p><span><span>Direction : Dorothée Adam-Mazard (Inuaprod) & Marie Kazeroni (LSCE-CNRS)</span></span></p> <p><span><span>Montage et édition : Thomas d’Aram</span></span></p> <p><span><span>Motion Design : Pauline Fuchs</span></span></p> <p><span><span>Co-production: DEEPICE & Inuaprod</span></span></p>
Focus Group for Block Chain for Subtitles
<p>Transcript of the focus group</p>
DEEPICE Stories Videos series - Insight into Ice & Climate - Videos with Italian subtitles
<p><em>DEEPICE Stories – Insights into Ice & Climate </em>is a series of 15 videos<em> </em>created in collaboration with the 15 PhD students of the European research project <a href="https://deepice.cnrs.fr/">DEEPICE</a>. These 3-minute educational video clips give an overview of scientific research on ice cores. <a href="https://deepice.cnrs.fr">https://deepice.cnrs.fr</a></p> <p><u>Credits</u></p> <p>Writing & presentation: Geunwoo Lee, Hanne Notø, Eirini Malegiannaki, Piers Larkman, Miguel Angel Sanchez Moreno, Lison Soussaintjean, Florian Painer, Niklas Kappelt, Lisa Ardoin, Inès Ollivier, Romilly Harris Stuart, Fyntan Shaw, Qinggang Gao, Ailsa Chung, Daniel Gunning</p> <p>Coordination : Marie Kazeroni (LSCE-CNRS)</p> <p>Direction: Dorothée Adam-Mazard (Inuaprod) & Marie Kazeroni (LSCE-CNRS)</p> <p>Editing: Thomas d’Aram</p> <p>Motion Design: Pauline Fuchs</p> <p>Co-production: DEEPICE & Inuaprod</p> <p>_____________________________________________</p> <p><em><span>DEEPICE Stories - Insights into Ice & Climate </span></em><span>è una serie di 15 video creati in collaborazione con i 15 dottorandi del progetto di ricerca europeo <a href="https://deepice.cnrs.fr/">DEEPICE</a>. Queste video didattici di 3 minuti, offrono una sintesi della ricerca scientifica sulle carote di ghiaccio. <a href="https://deepice.cnrs.fr">https://deepice.cnrs.fr</a></span></p> <p><span><span>Scrittura e presentazione : Geunwoo Lee, Hanne Notø, Eirini Malegiannaki, Piers Larkman, Miguel Angel Sanchez Moreno, Lison Soussaintjean, Florian Painer, Niklas Kappelt, Lisa Ardoin, Inès Ollivier, Romilly Harris Stuart, Fyntan Shaw, Qinggang Gao, Ailsa Chung, Daniel Gunning<br></span></span></p> <p><span><span>Coordinamento : Marie Kazeroni (LSCE-CNRS)</span></span></p> <p><span><span>Direzione : Dorothée Adam-Mazard (Inuaprod) & Marie Kazeroni (LSCE-CNRS)</span></span></p> <p><span><span>Montaggio : Thomas d’Aram</span></span></p> <p><span><span>Motion Design : Pauline Fuchs</span></span></p> <p>Coproduzione : <span><span>DEEPICE & Inuaprod</span></span></p>
DEEPICE Stories Videos series - Insight into Ice & Climate - Videos with Spanish subtitles
<p><em><span>DEEPICE Stories - Insights into Ice & Climate </span></em><span>es una serie de 15 vídeos creados en colaboración con los 15 estudiantes de doctorado del proyecto de ciencia europeo <a href="https://deepice.cnrs.fr/">DEEPICE</a>. Estos videoclips educativos de 3 minutos ofrecen una visión general de la ciencia sobre los testigos de hielo. <a href="https://deepice.cnrs.fr">https://deepice.cnrs.fr</a></span></p> <p><span><span>Presentación: Geunwoo Lee, Hanne Notø, Eirini Malegiannaki, Piers Larkman, Miguel Angel Sanchez Moreno, Lison Soussaintjean, Florian Painer, Niklas Kappelt, Lisa Ardoin, Inès Ollivier, Romilly Harris Stuart, Fyntan Shaw, Qinggang Gao, Ailsa Chung, Daniel Gunning<br></span></span></p> <p><span><span>Coordinación: Marie Kazeroni (LSCE-CNRS)</span></span></p> <p><span><span>Dirección: Dorothée Adam-Mazard (Inuaprod) & Marie Kazeroni (LSCE-CNRS)</span></span></p> <p><span><span>Montaje y edi</span></span>ción : <span><span>Thomas d’Aram</span></span></p> <p><span><span>Motion Design: Pauline Fuchs</span></span></p> <p><span><span>Coproducción: DEEPICE & Inuaprod</span></span></p>
SURE Project Subtitle Files
<p>Subtitle files (.xlsx format) from Experiment 1 and Experiment 2 from the project "SURE - Exploring Subtitle Reading Process with Eyetracking Technology", supported by a grant from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 702606.</p> <p>In each experiment, there are files in English, Polish and Spanish, with time codes, as used in the study.</p> <p>Each file contains three versions: subtitled at 12, 16 and 20 characters per second (cps).</p>
SubIMDB: A Structured Corpus of Subtitles
<p>Exploring language usage through frequency analysis in large corpora is a defining feature in most recent work in corpus and computational linguistics. From a psycholinguistic perspective, however, the corpora used in these contributions are often not representative of language usage: they are either domain-specific, limited in size, or extracted from unreliable sources. In an effort to address this limitation, we introduce SubIMDB, a corpus of everyday language spoken text we created which contains over 225 million words. The corpus was extracted from 38,102 subtitles of family, comedy and children movies and series, and is the first sizeable structured corpus of subtitles made available. Our experiments show that word frequency norms extracted from this corpus are more effective than those from well-known norms such as Kucera-Francis, HAL and SUBTLEXus in predicting various psycholinguistic properties of words, such as lexical decision times, familiarity, age of acquisition and simplicity. We also provide evidence that contradict the long-standing assumption that the ideal size for a corpus can be determined solely based on how well its word frequencies correlate with lexical decision times.</p>
[Dataset] An End User Based Study on Subtitling for the d/Deaf and Hard of Hearing in Turkey [Unpublished Master's Thesis]
<p>The dataset provided is from an unpublished master's thesis authored by Selma Akseki and supervised by Asst. Prof. Elif Ersözlü at Hacettepe University, Ankara (Türkiye). For more details see https://www.openaccess.hacettepe.edu.tr/xmlui/handle/11655/25767</p> <p>Abstract from the master's thesis reporting on the analysis of this dataset:</p> <p>Reception research in audiovisual translation (AVT), particularly on the<br> intersection between AVT and media accessibility (MA) has been a research<br> avenue to interest for translation scholars in the last couple of decades. However,<br> research in reception studies in countries like Turkey, where MA practices are<br> relatively new in terms of legislative mandates on the subject, are still scarce.<br> This thesis aims to contribute to the field by investigating the reception of subtitles<br> for the d/Deaf and hard of hearing (SDH) by the intended audience, Turkish<br> d/Deaf and hard of hearing (HOH) viewers. The present study places itself in the<br> intersection of Descriptive Translation Studies (DTS) and Reception Studies (RS)<br> within AVT. First, guidelines and current practices of SDH were investigated to<br> reveal the norms with a focus on specific parameters. Second, a questionnaire<br> was designed to elicit the opinions of viewers on these practices. The English<br> template of the Digital TV for All (DTV4ALL) questionnaire was adapted to the<br> Turkish context (Romero-Fresco, 2015). The project in which the original<br> questionnaire was used aimed to facilitate provision of access services and<br> provide feedback from viewers that could be relevant to stakeholders in improving<br> the quality of SDH. The Turkish questionnaire, designed with a similar objective<br> in mind, consisted of questions regarding demographic and personal data,<br> viewing habits and preferences, and opinions on particular SDH parameters.<br> Data was collected from 237 participants through online and paper<br> questionnaires. Findings were compared with previous similar studies and<br> discussed. In conclusion, as regards the specific SDH parameters investigated,<br> current practices seem to accomplish their skopos. The provision of more<br> subtitled programmes on free-to-air linear broadcast with a wider variety of types<br> of programmes, and offering of accessible versions with premieres of<br> programmes are areas that, according to the end users, could be improved on.</p>
Annotated educational videos and subtitles (EDUVSUM)
<p>We have collected educational videos with subtitles from three popular e-learning platforms: Edx,YouTube, and TIB AV-Portal that cover the following topics: crash course on history of science and engineering, computer science, python and web programming, machine learning and computer vision, Internet of things (IoT), and software engineering. In total, the current version of the dataset contains 98 videos with ground truth values annotated by a user with an academic background in computer science.</p> <p> </p> <p> </p> <p>Cite our work in order to use the resources (<a href="https://arxiv.org/abs/2010.13626">https://arxiv.org/abs/2010.13626</a> )</p> <p><a href="https://github.com/VideoAnalysis/EDUVSUM">https://github.com/VideoAnalysis/EDUVSUM</a></p> <p><a href="https://github.com/VideoAnalysis/VideoAnnotationTool">https://github.com/VideoAnalysis/VideoAnnotationTool</a></p> <p> </p> <pre><code>@article{ghauri2020eduvsum, title={Classification of Important Segments in Educational Videos using Multimodal Features}, author={Ghauri, Junaid Ahmed and Hakimov, Sherzod and Ewerth, Ralph}, Conference={International Workshop on Investigating Learning During Web Search (IWILDS 2020) co-located with CIKM}, year={2020} }</code></pre> <p> </p>
French verbal frequencies in the Open Subtitle corpus
<p>This repository provides frequencies for French verbal paradigm cells in the French Open Subtitles Corpus.</p>
SubComm Infographics - Subtitles: A Balancing Act
<p>An infographic describing the various challenges and considerations associated with subtitling.</p>
SubComm Infographics - Who Watches Subtitles?
<p>An infographic depicting different subtitle user profiles.</p>
SubComm Infographics - The Business of Subtitling
<p>An infographic listing various tasks that are a part of a subtitler's job.</p>
SubComm Infographics - Different Types of Subtitles
<p>An infographic desribing different types of subtitles.</p>
PICS: Subtitle Cardiac Dysfunction in Older Sepsis Survivors
ClinicalTrials.gov study NCT02276417. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Subtitled speech: Phenomenology of tickertape synesthesia
<p>Instropective description of ticker-tape synesthesia, and description of their perception when listening to noises, pseudowords and other stimuli.</p> <p>Here are included: the dataset of questionnaire answers, the audio stimuli (noises, including humann, animal and noises), and the english version of the questionnaire.</p>
Pivot subtitling of Korean dramas on Netflix Türkiye between 2015 and 2022
<p>This list provides detailed information on the pivot subtitling of Korean dramas on Netflix Türkiye between 2015 and 2022. It includes essential details such as the titles, release years on Netflix, subtitlers, the number of subtitlers involved, and the available translation methods. This list has been compiled for the article ‘Pivot Subtitling on Netflix: the Case of Squid Game’ to be published in <em><a href="https://www.jatjournal.org/">Journal of Audiovisual Translation</a></em>.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.