FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN
Ebrahim Ansari, Amittai Axelrod, Nguyen Bach, Ondřej Bojar, Roldano Cattoni, Fahim Dalvi, Nadir Durrani, Marcello Federico, Christian Federmann, Jiatao Gu, Fei Huang, Kevin Knight, Xutai Ma, Ajay Nagesh, Matteo Negri, Jan Niehues, Juan Pino, Elizabeth Salesky, Xing Shi, Sebastian Stüker, Marco Turchi, Alexander Waibel, Changhan Wang
Correct Metadata for
Abstract
The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2020) featured this year six challenge tracks: (i) Simultaneous speech translation, (ii) Video speech translation, (iii) Offline speech translation, (iv) Conversational speech translation, (v) Open domain translation, and (vi) Non-native speech translation. A total of teams participated in at least one of the tracks. This paper introduces each track’s goal, data and evaluation metrics, and reports the results of the received submissions.- Anthology ID:
- 2020.iwslt-1.1
- Original:
- 2020.iwslt-1.1v1
- Version 2:
- 2020.iwslt-1.1v2
- Volume:
- Proceedings of the 17th International Conference on Spoken Language Translation
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Marcello Federico, Alex Waibel, Kevin Knight, Satoshi Nakamura, Hermann Ney, Jan Niehues, Sebastian Stüker, Dekai Wu, Joseph Mariani, Francois Yvon
- Venue:
- IWSLT
- SIG:
- SIGSLT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1–34
- Language:
- URL:
- https://aclanthology.org/2020.iwslt-1.1/
- DOI:
- 10.18653/v1/2020.iwslt-1.1
- Bibkey:
- Cite (ACL):
- Ebrahim Ansari, Amittai Axelrod, Nguyen Bach, Ondřej Bojar, Roldano Cattoni, Fahim Dalvi, Nadir Durrani, Marcello Federico, Christian Federmann, Jiatao Gu, Fei Huang, Kevin Knight, Xutai Ma, Ajay Nagesh, Matteo Negri, Jan Niehues, Juan Pino, Elizabeth Salesky, Xing Shi, Sebastian Stüker, Marco Turchi, Alexander Waibel, and Changhan Wang. 2020. FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN. In Proceedings of the 17th International Conference on Spoken Language Translation, pages 1–34, Online. Association for Computational Linguistics.
- Cite (Informal):
- FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN (Ansari et al., IWSLT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.iwslt-1.1.pdf
Export citation
@inproceedings{ansari-etal-2020-findings,
title = "{FINDINGS} {OF} {THE} {IWSLT} 2020 {EVALUATION} {CAMPAIGN}",
author = {Ansari, Ebrahim and
Axelrod, Amittai and
Bach, Nguyen and
Bojar, Ond{\v{r}}ej and
Cattoni, Roldano and
Dalvi, Fahim and
Durrani, Nadir and
Federico, Marcello and
Federmann, Christian and
Gu, Jiatao and
Huang, Fei and
Knight, Kevin and
Ma, Xutai and
Nagesh, Ajay and
Negri, Matteo and
Niehues, Jan and
Pino, Juan and
Salesky, Elizabeth and
Shi, Xing and
St{\"u}ker, Sebastian and
Turchi, Marco and
Waibel, Alexander and
Wang, Changhan},
editor = {Federico, Marcello and
Waibel, Alex and
Knight, Kevin and
Nakamura, Satoshi and
Ney, Hermann and
Niehues, Jan and
St{\"u}ker, Sebastian and
Wu, Dekai and
Mariani, Joseph and
Yvon, Francois},
booktitle = "Proceedings of the 17th International Conference on Spoken Language Translation",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.iwslt-1.1/",
doi = "10.18653/v1/2020.iwslt-1.1",
pages = "1--34",
abstract = "The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2020) featured this year six challenge tracks: (i) Simultaneous speech translation, (ii) Video speech translation, (iii) Offline speech translation, (iv) Conversational speech translation, (v) Open domain translation, and (vi) Non-native speech translation. A total of teams participated in at least one of the tracks. This paper introduces each track{'}s goal, data and evaluation metrics, and reports the results of the received submissions."
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%0 Conference Proceedings %T FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN %A Ansari, Ebrahim %A Axelrod, Amittai %A Bach, Nguyen %A Bojar, Ondřej %A Cattoni, Roldano %A Dalvi, Fahim %A Durrani, Nadir %A Federico, Marcello %A Federmann, Christian %A Gu, Jiatao %A Huang, Fei %A Knight, Kevin %A Ma, Xutai %A Nagesh, Ajay %A Negri, Matteo %A Niehues, Jan %A Pino, Juan %A Salesky, Elizabeth %A Shi, Xing %A Stüker, Sebastian %A Turchi, Marco %A Waibel, Alexander %A Wang, Changhan %Y Federico, Marcello %Y Waibel, Alex %Y Knight, Kevin %Y Nakamura, Satoshi %Y Ney, Hermann %Y Niehues, Jan %Y Stüker, Sebastian %Y Wu, Dekai %Y Mariani, Joseph %Y Yvon, Francois %S Proceedings of the 17th International Conference on Spoken Language Translation %D 2020 %8 July %I Association for Computational Linguistics %C Online %F ansari-etal-2020-findings %X The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2020) featured this year six challenge tracks: (i) Simultaneous speech translation, (ii) Video speech translation, (iii) Offline speech translation, (iv) Conversational speech translation, (v) Open domain translation, and (vi) Non-native speech translation. A total of teams participated in at least one of the tracks. This paper introduces each track’s goal, data and evaluation metrics, and reports the results of the received submissions. %R 10.18653/v1/2020.iwslt-1.1 %U https://aclanthology.org/2020.iwslt-1.1/ %U https://doi.org/10.18653/v1/2020.iwslt-1.1 %P 1-34
Markdown (Informal)
[FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN](https://aclanthology.org/2020.iwslt-1.1/) (Ansari et al., IWSLT 2020)
- FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN (Ansari et al., IWSLT 2020)
ACL
- Ebrahim Ansari, Amittai Axelrod, Nguyen Bach, Ondřej Bojar, Roldano Cattoni, Fahim Dalvi, Nadir Durrani, Marcello Federico, Christian Federmann, Jiatao Gu, Fei Huang, Kevin Knight, Xutai Ma, Ajay Nagesh, Matteo Negri, Jan Niehues, Juan Pino, Elizabeth Salesky, Xing Shi, Sebastian Stüker, Marco Turchi, Alexander Waibel, and Changhan Wang. 2020. FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN. In Proceedings of the 17th International Conference on Spoken Language Translation, pages 1–34, Online. Association for Computational Linguistics.