@inproceedings{sakti-etal-2014-towards,
title = "Towards Multilingual Conversations in the Medical Domain: Development of Multilingual Medical Data and A Network-based {ASR} System",
author = "Sakti, Sakriani and
Kubo, Keigo and
Matsumiya, Sho and
Neubig, Graham and
Toda, Tomoki and
Nakamura, Satoshi and
Adachi, Fumihiro and
Isotani, Ryosuke",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/709_Paper.pdf",
pages = "2639--2643",
abstract = "This paper outlines the recent development on multilingual medical data and multilingual speech recognition system for network-based speech-to-speech translation in the medical domain. The overall speech-to-speech translation (S2ST) system was designed to translate spoken utterances from a given source language into a target language in order to facilitate multilingual conversations and reduce the problems caused by language barriers in medical situations. Our final system utilizes a weighted finite-state transducers with n-gram language models. Currently, the system successfully covers three languages: Japanese, English, and Chinese. The difficulties involved in connecting Japanese, English and Chinese speech recognition systems through Web servers will be discussed, and the experimental results in simulated medical conversation will also be presented.",
}
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%0 Conference Proceedings
%T Towards Multilingual Conversations in the Medical Domain: Development of Multilingual Medical Data and A Network-based ASR System
%A Sakti, Sakriani
%A Kubo, Keigo
%A Matsumiya, Sho
%A Neubig, Graham
%A Toda, Tomoki
%A Nakamura, Satoshi
%A Adachi, Fumihiro
%A Isotani, Ryosuke
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F sakti-etal-2014-towards
%X This paper outlines the recent development on multilingual medical data and multilingual speech recognition system for network-based speech-to-speech translation in the medical domain. The overall speech-to-speech translation (S2ST) system was designed to translate spoken utterances from a given source language into a target language in order to facilitate multilingual conversations and reduce the problems caused by language barriers in medical situations. Our final system utilizes a weighted finite-state transducers with n-gram language models. Currently, the system successfully covers three languages: Japanese, English, and Chinese. The difficulties involved in connecting Japanese, English and Chinese speech recognition systems through Web servers will be discussed, and the experimental results in simulated medical conversation will also be presented.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/709_Paper.pdf
%P 2639-2643
Markdown (Informal)
[Towards Multilingual Conversations in the Medical Domain: Development of Multilingual Medical Data and A Network-based ASR System](http://www.lrec-conf.org/proceedings/lrec2014/pdf/709_Paper.pdf) (Sakti et al., LREC 2014)
ACL
- Sakriani Sakti, Keigo Kubo, Sho Matsumiya, Graham Neubig, Tomoki Toda, Satoshi Nakamura, Fumihiro Adachi, and Ryosuke Isotani. 2014. Towards Multilingual Conversations in the Medical Domain: Development of Multilingual Medical Data and A Network-based ASR System. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2639–2643, Reykjavik, Iceland. European Language Resources Association (ELRA).