Silvestre-Cerdà, Joan Albert; Juan, Alfons; Civera, Jorge Different Contributions to Cost-Effective Transcription and Translation of Video Lectures Inproceedings Proc. of IX Jornadas en Tecnología del Habla and V Iberian SLTech Workshop (IberSpeech 2016), pp. 313-319, Lisbon (Portugal), 2016, ISBN: 978-3-319-49168-4 . Abstract | Links | BibTeX | Tags: Automatic Speech Recognition, Automatic transcription and translation, Machine Translation, Video Lectures @inproceedings{Silvestre-Cerdà2016b,
title = {Different Contributions to Cost-Effective Transcription and Translation of Video Lectures},
author = {Joan Albert Silvestre-Cerdà and Alfons Juan and Jorge Civera},
url = {http://www.mllp.upv.es/wp-content/uploads/2016/11/poster.pdf
http://www.mllp.upv.es/wp-content/uploads/2016/11/paper.pdf
http://hdl.handle.net/10251/62194},
isbn = {978-3-319-49168-4 },
year = {2016},
date = {2016-11-24},
booktitle = {Proc. of IX Jornadas en Tecnología del Habla and V Iberian SLTech Workshop (IberSpeech 2016)},
pages = {313-319},
address = {Lisbon (Portugal)},
abstract = {In recent years, on-line multimedia repositories have experiencied
a strong growth that have made them consolidated as essential
knowledge assets, especially in the area of education, where large repositories
of video lectures have been built in order to complement or even
replace traditional teaching methods. However, most of these video lectures
are neither transcribed nor translated due to a lack of cost-effective
solutions to do so in a way that gives accurate enough results. Solutions
of this kind are clearly necessary in order to make these lectures accessible
to speakers of different languages and to people with hearing
disabilities, among many other benefits and applications.
For this reason, the main aim of this thesis is to develop a cost-effective
solution capable of transcribing and translating video lectures to a reasonable
degree of accuracy. More specifically, we address the integration
of state-of-the-art techniques in Automatic Speech Recognition and Machine
Translation into large video lecture repositories to generate highquality
multilingual video subtitles without human intervention and at
a reduced computational cost. Also, we explore the potential benefits of
the exploitation of the information that we know a priori about these
repositories, that is, lecture-specific knowledge such as speaker, topic
or slides, to create specialised, in-domain transcription and translation
systems by means of massive adaptation techniques.
The proposed solutions have been tested in real-life scenarios by carrying
out several objective and subjective evaluations, obtaining very
positive results. The main outcome derived from this multidisciplinary
thesis, The transLectures-UPV Platform, has been publicly released as an
open-source software, and, at the time of writing, it is serving automatic
transcriptions and translations for several thousands of video lectures in
many Spanish and European universities and institutions.},
keywords = {Automatic Speech Recognition, Automatic transcription and translation, Machine Translation, Video Lectures},
pubstate = {published},
tppubtype = {inproceedings}
}
In recent years, on-line multimedia repositories have experiencied
a strong growth that have made them consolidated as essential
knowledge assets, especially in the area of education, where large repositories
of video lectures have been built in order to complement or even
replace traditional teaching methods. However, most of these video lectures
are neither transcribed nor translated due to a lack of cost-effective
solutions to do so in a way that gives accurate enough results. Solutions
of this kind are clearly necessary in order to make these lectures accessible
to speakers of different languages and to people with hearing
disabilities, among many other benefits and applications.
For this reason, the main aim of this thesis is to develop a cost-effective
solution capable of transcribing and translating video lectures to a reasonable
degree of accuracy. More specifically, we address the integration
of state-of-the-art techniques in Automatic Speech Recognition and Machine
Translation into large video lecture repositories to generate highquality
multilingual video subtitles without human intervention and at
a reduced computational cost. Also, we explore the potential benefits of
the exploitation of the information that we know a priori about these
repositories, that is, lecture-specific knowledge such as speaker, topic
or slides, to create specialised, in-domain transcription and translation
systems by means of massive adaptation techniques.
The proposed solutions have been tested in real-life scenarios by carrying
out several objective and subjective evaluations, obtaining very
positive results. The main outcome derived from this multidisciplinary
thesis, The transLectures-UPV Platform, has been publicly released as an
open-source software, and, at the time of writing, it is serving automatic
transcriptions and translations for several thousands of video lectures in
many Spanish and European universities and institutions. |