Publications

@inproceedings{valor2015efficient,
title = {Efficient Generation of High-Quality Multilingual Subtitles for Video Lecture Repositories},
author = {Valor Miró, Juan Daniel and Silvestre-Cerdà, Joan Albert and Civera, Jorge and Turró, Carlos and Juan, Alfons},
url = {http://link.springer.com/chapter/10.1007/978-3-319-24258-3_44
http://www.mllp.upv.es/wp-content/uploads/2016/03/paper.pdf
},
isbn = {978-3-319-24258-3},
year = {2015},
date = {2015-09-17},
booktitle = {Proc. of 10th European Conf. on Technology Enhanced Learning (EC-TEL 2015)},
pages = {485--490},
address = {Toledo (Spain)},
abstract = {Video lectures are a valuable educational tool in higher education to support or replace face-to-face lectures in active learning strategies. In 2007 the Universitat Polit‘ecnica de Val‘encia (UPV) implemented its video lecture capture system, resulting in a high quality educational video repository, called poliMedia, with more than 10.000 mini lectures created by 1.373 lecturers. Also, in the framework of the European project transLectures, UPV has automatically generated transcriptions and translations in Spanish, Catalan and English for all videos included in the poliMedia video repository. transLectures’s objective responds to the widely-recognised need for subtitles to be provided with video lectures, as an essential service for non-native speakers and hearing impaired persons, and to allow advanced repository functionalities. Although high-quality automatic transcriptions and translations were generated in transLectures, they were not error-free. For this reason, lecturers need to manually review video subtitles to guarantee the absence of errors. The aim of this study is to evaluate the efficiency of the manual review process from automatic subtitles in comparison with the conventional generation of video subtitles from scratch. The reported results clearly indicate the convenience of providing automatic subtitles as a first step in the generation of video subtitles and the significant savings in time of up to almost 75% involved in reviewing subtitles.},
keywords = {Automatic Speech Recognition, Docencia en Red, Efficient video subtitling, Polimedia, Statistical machine translation, video lecture repositories},
pubstate = {published},
tppubtype = {inproceedings}
}

@misc{mllpttp,
title = {MLLP Transcription and Translation Platform},
author = {Pérez González de Martos, Alejandro and Silvestre-Cerdà, Joan Albert and Valor Miró, Juan Daniel and Civera, Jorge and Juan, Alfons},
url = {http://hdl.handle.net/10251/65747
http://www.mllp.upv.es/wp-content/uploads/2015/09/ttp_platform_demo_ectel2015.pdf
http://ectel2015.httc.de/index.php?id=722},
year = {2015},
date = {2015-09-16},
booktitle = {Tenth European Conference On Technology Enhanced Learning (EC-TEL 2015)},
abstract = {This paper briefly presents the main features of MLLP’s Transcription and Translation Platform, which uses state-of-the-art automatic speech recognition and machine translation systems to generate multilingual subtitles of educational audiovisual and textual content. It has proven to reduce user effort up to 1/3 of the time needed to generate transcriptions and translations from scratch.},
note = {Short paper for demo presentation accepted at 10th European Conf. on Technology Enhanced Learning (EC-TEL 2015), Toledo (Spain), 2015.},
keywords = {Automatic Speech Recognition, Docencia en Red, Document translation, Efficient video subtitling, Machine Translation, MLLP, Post-editing, Video Lectures},
pubstate = {published},
tppubtype = {misc}
}