SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation

Mercedes Garcia Martinez; Karan Singla; Aniruddha Tammewar; Bartolomé  Mesa-Lao; Ankita Thakur; M. A. Anusuya; Banglore Srinivas; Michael Carl

SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation

Mercedes Garcia Martinez, Karan Singla, Aniruddha Tammewar, Bartolomé Mesa-Lao, Ankita Thakur, M. A. Anusuya, Banglore Srinivas, Michael Carl

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Abstract

Typing has traditionally been the only input method used by human translators working with computer-assisted translation (CAT) tools. However, speech is a natural communication channel for humans and, in principle, it should be faster and easier than typing from a keyboard. This contribution investigates the integration of automatic speech recognition (ASR) in a CAT workbench testing its real use by human translators while post-editing machine translation (MT) outputs. This paper also explores the use of MT combined with ASR in order to improve recognition accuracy in a workbench integrating eye-tracking functionalities to collect process-oriented information about translators’ performance.

Originalsprog	Engelsk
Titel	Proceedings of the 17th Annual Conference of the European Association for Machine Translation : EAMT2014
Redaktører	Marko Tadić, Philipp Koehn, Johann Roturier, Andy Way
Udgivelsessted	Basel
Forlag	European Association for Machine Translation
Publikationsdato	2014
Sider	81-88
ISBN (Trykt)	9789535537533
Status	Udgivet - 2014
Begivenhed	The 17th Annual Conference of the European Association for Machine Translation. EAMT 2014 - The Centre for Advanced Academic Studies , Dubrovnik, Kroatien Varighed: 16 jun. 2014 → 18 jun. 2014 Konferencens nummer: 17 http://hnk.ffzg.hr/eamt2014/

Konference

Konference	The 17th Annual Conference of the European Association for Machine Translation. EAMT 2014
Nummer	17
Lokation	The Centre for Advanced Academic Studies
Land/Område	Kroatien
By	Dubrovnik
Periode	16/06/2014 → 18/06/2014
Internetadresse	http://hnk.ffzg.hr/eamt2014/

Adgang til dokumentet

http://hnk.ffzg.hr/eamt2014/EAMT2014_proceedings.pdf

Handle.net

Persistent link

Citationsformater

Martinez, M. G., Singla, K., Tammewar, A., Mesa-Lao, B., Thakur, A., Anusuya, M. A., Srinivas, B., & Carl, M. (2014). SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation. I M. Tadić, P. Koehn, J. Roturier, & A. Way (red.), Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014 (s. 81-88). European Association for Machine Translation. http://hnk.ffzg.hr/eamt2014/EAMT2014_proceedings.pdf

Martinez, Mercedes Garcia ; Singla, Karan ; Tammewar, Aniruddha et al. / SEECAT : ASR & Eye-tracking Enabled Computer Assisted Translation. Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014. red. / Marko Tadić ; Philipp Koehn ; Johann Roturier ; Andy Way. Basel : European Association for Machine Translation, 2014. s. 81-88

@inproceedings{a651a43c78334755829aa2a38b6c57f1,

title = "SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation",

abstract = "Typing has traditionally been the only input method used by human translators working with computer-assisted translation (CAT) tools. However, speech is a natural communication channel for humans and, in principle, it should be faster and easier than typing from a keyboard. This contribution investigates the integration of automatic speech recognition (ASR) in a CAT workbench testing its real use by human translators while post-editing machine translation (MT) outputs. This paper also explores the use of MT combined with ASR in order to improve recognition accuracy in a workbench integrating eye-tracking functionalities to collect process-oriented information about translators{\textquoteright} performance.",

author = "Martinez, {Mercedes Garcia} and Karan Singla and Aniruddha Tammewar and Bartolom{\'e} Mesa-Lao and Ankita Thakur and Anusuya, {M. A.} and Banglore Srinivas and Michael Carl",

year = "2014",

language = "English",

isbn = "9789535537533",

pages = "81--88",

editor = "Marko Tadi{\'c} and Philipp Koehn and Johann Roturier and Andy Way",

booktitle = "Proceedings of the 17th Annual Conference of the European Association for Machine Translation",

publisher = "European Association for Machine Translation",

address = "Switzerland",

note = "The 17th Annual Conference of the European Association for Machine Translation. EAMT 2014 ; Conference date: 16-06-2014 Through 18-06-2014",

url = "http://hnk.ffzg.hr/eamt2014/",

}

Martinez, MG, Singla, K, Tammewar, A, Mesa-Lao, B, Thakur, A, Anusuya, MA, Srinivas, B & Carl, M 2014, SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation. i M Tadić, P Koehn, J Roturier & A Way (red), Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014. European Association for Machine Translation, Basel, s. 81-88, The 17th Annual Conference of the European Association for Machine Translation. EAMT 2014, Dubrovnik, Kroatien, 16/06/2014. <http://hnk.ffzg.hr/eamt2014/EAMT2014_proceedings.pdf>

SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation. / Martinez, Mercedes Garcia; Singla, Karan; Tammewar, Aniruddha et al.
Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014. red. / Marko Tadić; Philipp Koehn; Johann Roturier; Andy Way. Basel: European Association for Machine Translation, 2014. s. 81-88.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - SEECAT

T2 - The 17th Annual Conference of the European Association for Machine Translation. EAMT 2014

AU - Martinez, Mercedes Garcia

AU - Singla, Karan

AU - Tammewar, Aniruddha

AU - Mesa-Lao, Bartolomé

AU - Thakur, Ankita

AU - Anusuya, M. A.

AU - Srinivas, Banglore

AU - Carl, Michael

N1 - Conference code: 17

PY - 2014

Y1 - 2014

N2 - Typing has traditionally been the only input method used by human translators working with computer-assisted translation (CAT) tools. However, speech is a natural communication channel for humans and, in principle, it should be faster and easier than typing from a keyboard. This contribution investigates the integration of automatic speech recognition (ASR) in a CAT workbench testing its real use by human translators while post-editing machine translation (MT) outputs. This paper also explores the use of MT combined with ASR in order to improve recognition accuracy in a workbench integrating eye-tracking functionalities to collect process-oriented information about translators’ performance.

AB - Typing has traditionally been the only input method used by human translators working with computer-assisted translation (CAT) tools. However, speech is a natural communication channel for humans and, in principle, it should be faster and easier than typing from a keyboard. This contribution investigates the integration of automatic speech recognition (ASR) in a CAT workbench testing its real use by human translators while post-editing machine translation (MT) outputs. This paper also explores the use of MT combined with ASR in order to improve recognition accuracy in a workbench integrating eye-tracking functionalities to collect process-oriented information about translators’ performance.

M3 - Article in proceedings

SN - 9789535537533

SP - 81

EP - 88

BT - Proceedings of the 17th Annual Conference of the European Association for Machine Translation

A2 - Tadić, Marko

A2 - Koehn, Philipp

A2 - Roturier, Johann

A2 - Way, Andy

PB - European Association for Machine Translation

CY - Basel

Y2 - 16 June 2014 through 18 June 2014

ER -