@inproceedings{dessloch-etal-2018-kit,
title = "{KIT} Lecture Translator: Multilingual Speech Translation with One-Shot Learning",
author = {Dessloch, Florian and
Ha, Thanh-Le and
M{\"u}ller, Markus and
Niehues, Jan and
Nguyen, Thai-Son and
Pham, Ngoc-Quan and
Salesky, Elizabeth and
Sperber, Matthias and
St{\"u}ker, Sebastian and
Zenkel, Thomas and
Waibel, Alexander},
editor = "Zhao, Dongyan",
booktitle = "Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations",
month = aug,
year = "2018",
address = "Santa Fe, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/C18-2020",
pages = "89--93",
abstract = "In today{'}s globalized world we have the ability to communicate with people across the world. However, in many situations the language barrier still presents a major issue. For example, many foreign students coming to KIT to study are initially unable to follow a lecture in German. Therefore, we offer an automatic simultaneous interpretation service for students. To fulfill this task, we have developed a low-latency translation system that is adapted to lectures and covers several language pairs. While the switch from traditional Statistical Machine Translation to Neural Machine Translation (NMT) significantly improved performance, to integrate NMT into the speech translation framework required several adjustments. We have addressed the run-time constraints and different types of input. Furthermore, we utilized one-shot learning to easily add new topic-specific terms to the system. Besides better performance, NMT also enabled us increase our covered languages through multilingual NMT. {\%} Combining these techniques, we are able to provide an adapted speech translation system for several European languages.",
}
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<abstract>In today’s globalized world we have the ability to communicate with people across the world. However, in many situations the language barrier still presents a major issue. For example, many foreign students coming to KIT to study are initially unable to follow a lecture in German. Therefore, we offer an automatic simultaneous interpretation service for students. To fulfill this task, we have developed a low-latency translation system that is adapted to lectures and covers several language pairs. While the switch from traditional Statistical Machine Translation to Neural Machine Translation (NMT) significantly improved performance, to integrate NMT into the speech translation framework required several adjustments. We have addressed the run-time constraints and different types of input. Furthermore, we utilized one-shot learning to easily add new topic-specific terms to the system. Besides better performance, NMT also enabled us increase our covered languages through multilingual NMT. % Combining these techniques, we are able to provide an adapted speech translation system for several European languages.</abstract>
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%0 Conference Proceedings
%T KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning
%A Dessloch, Florian
%A Ha, Thanh-Le
%A Müller, Markus
%A Niehues, Jan
%A Nguyen, Thai-Son
%A Pham, Ngoc-Quan
%A Salesky, Elizabeth
%A Sperber, Matthias
%A Stüker, Sebastian
%A Zenkel, Thomas
%A Waibel, Alexander
%Y Zhao, Dongyan
%S Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico
%F dessloch-etal-2018-kit
%X In today’s globalized world we have the ability to communicate with people across the world. However, in many situations the language barrier still presents a major issue. For example, many foreign students coming to KIT to study are initially unable to follow a lecture in German. Therefore, we offer an automatic simultaneous interpretation service for students. To fulfill this task, we have developed a low-latency translation system that is adapted to lectures and covers several language pairs. While the switch from traditional Statistical Machine Translation to Neural Machine Translation (NMT) significantly improved performance, to integrate NMT into the speech translation framework required several adjustments. We have addressed the run-time constraints and different types of input. Furthermore, we utilized one-shot learning to easily add new topic-specific terms to the system. Besides better performance, NMT also enabled us increase our covered languages through multilingual NMT. % Combining these techniques, we are able to provide an adapted speech translation system for several European languages.
%U https://aclanthology.org/C18-2020
%P 89-93
Markdown (Informal)
[KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning](https://aclanthology.org/C18-2020) (Dessloch et al., COLING 2018)
ACL
- Florian Dessloch, Thanh-Le Ha, Markus Müller, Jan Niehues, Thai-Son Nguyen, Ngoc-Quan Pham, Elizabeth Salesky, Matthias Sperber, Sebastian Stüker, Thomas Zenkel, and Alexander Waibel. 2018. KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 89–93, Santa Fe, New Mexico. Association for Computational Linguistics.