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Interpreters facilitate multi-lingual meetings but the affordable set of languages is often smaller than what is needed.
K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, “Bleu: a method for automatic evaluation of machine translation,” in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics . Association for Computational Linguistics, 2002, pp. 311–318
2002
Earlier work this paper cites.
P. Koehn, “Europarl: A Parallel Corpus for Statistical Machine Translation,” in Conference Proceedings: the tenth Machine Translation Summit , AAMT. AAMT, 2005, pp. 79–86
2005
Earlier work this paper cites.
A. Sandrelli and C. Bendazzoli, “Tagging a corpus of interpreted speeches: the European parliament interpreting corpus (EPIC),” in Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06) . European Language Resources Association (ELRA), 2006
2006
Earlier work this paper cites.
P. Koehn and al., “Moses: Open source toolkit for statistical machine translation,” in Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions . Association for Computational Linguistics, 2007, pp. 177–180
2007
Earlier work this paper cites.
E. Cho, J. Niehues, and A. H. Waibel, “Segmentation and punctuation prediction in speech language translation using a monolingual translation system,” in IWSLT , 2012
2012
Earlier work this paper cites.
M. Rouvier, P. Gay, E. Khoury, T. Merlin, and S. Meignier, “An open-source state-of-the-art toolbox for broadcast news diarization,” in in Proc. of Interspeech , 2013
2013
Earlier work this paper cites.
E. Cho, C. Fügen, T. Hermann, K. Kilgour, M. Mediani, C. Mohr, J. Niehues, K. Rottmann, C. Saam, S. Stüker, and A. Waibel, “A real-world system for simultaneous translation of german lectures,” pp. 3473–3477, 01 2013
2013
Earlier work this paper cites.
C. Dyer, V. Chahuneau, and N. A. Smith, “A simple, fast, and effective reparameterization of IBM model 2,” in Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, 2013, pp. 644–648
2013
Earlier work this paper cites.
U. D. Reichel, “Language-independent grapheme-phoneme conversion and word stress assignment as a web service,” in Elektronische Sprachverarbeitung 2014 , R. Hoffmann, Ed. Dresden, Germany: TUDpress, 2014, vol. 71, pp. 42–49
2014
Earlier work this paper cites.
B. Defrancq, “Corpus-based research into the presumed effects of short evs,” Interpreting , vol. 17, 04 2015
2015
Earlier work this paper cites.
H. He, J. Boyd-Graber, and H. Daumé III, “Interpretese vs. translationese: The uniqueness of human strategies in simultaneous interpretation,” in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, 2016, pp. 971–976
2016
Cited alongside, same era.
S. Bernardini, A. Ferraresi, and M. Milicevic, “From EPIC to EPTIC — Exploring simplification in interpreting and translation from an intermodal perspective,” Target , vol. 28, pp. 61–86, 05 2016
2016
Cited alongside, same era.
Y. Kikuchi, G. Neubig, R. Sasano, H. Takamura, and M. Okumura, “Controlling output length in neural encoder-decoders,” in Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, 2016, pp. 1328–1338
2016
Cited alongside, same era.
J. Niehues, N.-Q. Pham, T.-L. Ha, M. Sperber, and A. Waibel, “Low-latency neural speech translation,” in Proc. Interspeech 2018 , 2018, pp. 1293–1297. [Online]. Available: http://dx.doi.org/10.21437/Interspeech.2018-1055
2018
Later among the works it cites.
2018
Later among the works it cites.
J. Pan, “The Chinese/English political interpreting corpus (CEPIC): A new electronic resource for translators and interpreters,” in Proceedings of the Human-Informed Translation and Interpreting Technology Workshop (HiT-IT 2019) . Incoma Ltd., Shoumen, Bulgaria, 2019, pp. 82–88
2019
Later among the works it cites.
S. Takase and N. Okazaki, “Positional encoding to control output sequence length.” Association for Computational Linguistics, 2019, pp. 3999–4004
2019
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O. Bojar, O. Dušek, T. Kocmi, J. Libovický, M. Novák, M. Popel, R. Sudarikov, and D. Variš, “CzEng 1.6: Enlarged Czech-English Parallel Corpus with Processing Tools Dockered,” in Text, Speech, and Dialogue: 19th International Conference, TSD 2016 , no. 9924, Masaryk University. Springer International Publishing, 2016, pp. 231–238
2016
Cited alongside, same era.
P. Lison and J. Tiedemann, “OpenSubtitles2016: Extracting large parallel corpora from movie and TV subtitles,” in Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16) . European Language Resources Association (ELRA), 2016, pp. 923–929
2016
Cited alongside, same era.
M. Müller, T. S. Nguyen, J. Niehues, E. Cho, B. Krüger, T.-L. Ha, K. Kilgour, M. Sperber, M. Mediani, S. Stüker, and A. Waibel, “Lecture translator - speech translation framework for simultaneous lecture translation.” Association for Computational Linguistics, 2016, pp. 82–86
2016
Cited alongside, same era.
I. Temnikova, A. Abdelali, S. Hedaya, S. Vogel, and A. Al Daher, “Interpreting strategies annotation in the WAW corpus,” in Proceedings of the Workshop Human-Informed Translation and Interpreting Technology . Association for Computational Linguistics, Shoumen, Bulgaria, 2017, pp. 36–43
2017
Cited alongside, same era.
T. Kisler, U. Reichel, and F. Schiel, “Multilingual processing of speech via web services,” Computer Speech & Language , vol. 45, pp. 326 – 347, 2017
2017
Cited alongside, same era.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in Neural Information Processing Systems 30 , I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Eds. Curran Associates, Inc., 2017, pp. 6000–6010
2017
Cited alongside, same era.
M. Junczys-Dowmunt, R. Grundkiewicz, T. Dwojak, H. Hoang, K. Heafield, T. Neckermann, F. Seide, U. Germann, A. Fikri Aji, N. Bogoychev, A. F. T. Martins, and A. Birch, “Marian: Fast neural machine translation in C++,” in Proceedings of ACL 2018, System Demonstrations . Association for Computational Linguistics, 2018, pp. 116–121
2018
Cited alongside, same era.
Later among the works it cites.
M. Ma and al., “STACL: Simultaneous translation with implicit anticipation and controllable latency using prefix-to-prefix framework.” Association for Computational Linguistics, 2019, pp. 3025–3036
2019
Later among the works it cites.
J. Iranzo-Sánchez, J. A. Silvestre-Cerdà, J. Jorge, N. Roselló, A. Giménez, A. Sanchis, J. Civera, and A. Juan, “Europarl-st: A multilingual corpus for speech translation of parliamentary debates,” in ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2020, pp. 8229–8233
2020
Later among the works it cites.
S. M. Lakew, “Multilingual neural machine translation for low resource languages,” Ph.D. dissertation, University of Trento, 2020
2020
Later among the works it cites.
N. Arivazhagan, C. Cherry, I. Te, W. Macherey, P. Baljekar, and G. F. Foster, “Re-translation strategies for long form, simultaneous, spoken language translation,” ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pp. 7919–7923, 2020
2020
Later among the works it cites.
D. Macháček, J. Kratochvíl, S. Sagar, M. Žilinec, O. Bojar, T.-S. Nguyen, F. Schneider, P. Williams, and Y. Yao, “ELITR non-native speech translation at IWSLT 2020,” in Proceedings of the 17th International Conference on Spoken Language Translation . Association for Computational Linguistics, 2020, pp. 200–208
2020
Later among the works it cites.
T.-S. Nguyen, S. Stueker, and A. Waibel, “Super-human performance in online low-latency recognition of conversational speech,” 2021
2021
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