@book{
 title = {Efficient generation of high-quality multilingual subtitles for video lecture repositories},
 type = {book},
 year = {2015},
 source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 identifiers = {[object Object]},
 keywords = {Automatic speech recognition,Efficient video subtitling,Machine translation,Video lecture repositories},
 pages = {485-490},
 volume = {9307},
 id = {03010150-aeff-3fce-9dc4-cb2b7066f098},
 created = {2016-04-20T17:15:04.000Z},
 file_attached = {false},
 profile_id = {380370e0-7486-3bbd-8fa8-e97f3f51b4c1},
 last_modified = {2016-04-20T17:15:04.000Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 abstract = {© Springer International Publishing Switzerland 2015. 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.},
 bibtype = {book},
 author = {Miró, J.D.V. and Silvestre-Cerdá, J.A. and Civera, J. and Turró, C. and Juan, A.}
}

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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.","bibtype":"book","author":"Miró, J.D.V. and Silvestre-Cerdá, J.A. and Civera, J. and Turró, C. and Juan, A.","bibtex":"@book{\n title = {Efficient generation of high-quality multilingual subtitles for video lecture repositories},\n type = {book},\n year = {2015},\n source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\n identifiers = {[object Object]},\n keywords = {Automatic speech recognition,Efficient video subtitling,Machine translation,Video lecture repositories},\n pages = {485-490},\n volume = {9307},\n id = {03010150-aeff-3fce-9dc4-cb2b7066f098},\n created = {2016-04-20T17:15:04.000Z},\n file_attached = {false},\n profile_id = {380370e0-7486-3bbd-8fa8-e97f3f51b4c1},\n last_modified = {2016-04-20T17:15:04.000Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n abstract = {© Springer International Publishing Switzerland 2015. 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.},\n bibtype = {book},\n author = {Miró, J.D.V. and Silvestre-Cerdá, J.A. and Civera, J. and Turró, C. and Juan, A.}\n}","author_short":["Miró, J.","Silvestre-Cerdá, J.","Civera, J.","Turró, C.","Juan, A."],"bibbaseid":"mir-silvestrecerd-civera-turr-juan-efficientgenerationofhighqualitymultilingualsubtitlesforvideolecturerepositories-2015","role":"author","urls":{},"keyword":["Automatic speech recognition","Efficient video subtitling","Machine translation","Video lecture repositories"],"downloads":0,"html":""},"search_terms":["efficient","generation","high","quality","multilingual","subtitles","video","lecture","repositories","miró","silvestre-cerdá","civera","turró","juan"],"keywords":["automatic speech recognition","efficient video subtitling","machine translation","video lecture repositories"],"authorIDs":[]}