@inproceedings{temnikova-etal-2017-interpreting,
title = "Interpreting Strategies Annotation in the {WAW} Corpus",
author = "Temnikova, Irina and
Abdelali, Ahmed and
Hedaya, Samy and
Vogel, Stephan and
Al Daher, Aishah",
editor = "Temnikova, Irina and
Orasan, Constantin and
Pastor, Gloria Corpas and
Vogel, Stephan",
booktitle = "Proceedings of the Workshop Human-Informed Translation and Interpreting Technology",
month = sep,
year = "2017",
address = "Varna, Bulgaria",
publisher = "Association for Computational Linguistics, Shoumen, Bulgaria",
url = "https://doi.org/10.26615/978-954-452-042-7_005",
doi = "10.26615/978-954-452-042-7_005",
pages = "36--43",
abstract = "With the aim to teach our automatic speech-to-text translation system human interpreting strategies, our first step is to identify which interpreting strategies are most often used in the language pair of our interest (English-Arabic). In this article we run an automatic analysis of a corpus of parallel speeches and their human interpretations, and provide the results of manually annotating the human interpreting strategies in a sample of the corpus. We give a glimpse of the corpus, whose value surpasses the fact that it contains a high number of scientific speeches with their interpretations from English into Arabic, as it also provides rich information about the interpreters. We also discuss the difficulties, which we encountered on our way, as well as our solutions to them: our methodology for manual re-segmentation and alignment of parallel segments, the choice of annotation tool, and the annotation procedure. Our annotation findings explain the previously extracted specific statistical features of the interpreted corpus (compared with a translation one) as well as the quality of interpretation provided by different interpreters.",
}
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<abstract>With the aim to teach our automatic speech-to-text translation system human interpreting strategies, our first step is to identify which interpreting strategies are most often used in the language pair of our interest (English-Arabic). In this article we run an automatic analysis of a corpus of parallel speeches and their human interpretations, and provide the results of manually annotating the human interpreting strategies in a sample of the corpus. We give a glimpse of the corpus, whose value surpasses the fact that it contains a high number of scientific speeches with their interpretations from English into Arabic, as it also provides rich information about the interpreters. We also discuss the difficulties, which we encountered on our way, as well as our solutions to them: our methodology for manual re-segmentation and alignment of parallel segments, the choice of annotation tool, and the annotation procedure. Our annotation findings explain the previously extracted specific statistical features of the interpreted corpus (compared with a translation one) as well as the quality of interpretation provided by different interpreters.</abstract>
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%0 Conference Proceedings
%T Interpreting Strategies Annotation in the WAW Corpus
%A Temnikova, Irina
%A Abdelali, Ahmed
%A Hedaya, Samy
%A Vogel, Stephan
%A Al Daher, Aishah
%Y Temnikova, Irina
%Y Orasan, Constantin
%Y Pastor, Gloria Corpas
%Y Vogel, Stephan
%S Proceedings of the Workshop Human-Informed Translation and Interpreting Technology
%D 2017
%8 September
%I Association for Computational Linguistics, Shoumen, Bulgaria
%C Varna, Bulgaria
%F temnikova-etal-2017-interpreting
%X With the aim to teach our automatic speech-to-text translation system human interpreting strategies, our first step is to identify which interpreting strategies are most often used in the language pair of our interest (English-Arabic). In this article we run an automatic analysis of a corpus of parallel speeches and their human interpretations, and provide the results of manually annotating the human interpreting strategies in a sample of the corpus. We give a glimpse of the corpus, whose value surpasses the fact that it contains a high number of scientific speeches with their interpretations from English into Arabic, as it also provides rich information about the interpreters. We also discuss the difficulties, which we encountered on our way, as well as our solutions to them: our methodology for manual re-segmentation and alignment of parallel segments, the choice of annotation tool, and the annotation procedure. Our annotation findings explain the previously extracted specific statistical features of the interpreted corpus (compared with a translation one) as well as the quality of interpretation provided by different interpreters.
%R 10.26615/978-954-452-042-7_005
%U https://doi.org/10.26615/978-954-452-042-7_005
%P 36-43
Markdown (Informal)
[Interpreting Strategies Annotation in the WAW Corpus](https://doi.org/10.26615/978-954-452-042-7_005) (Temnikova et al., RANLP 2017)
ACL
- Irina Temnikova, Ahmed Abdelali, Samy Hedaya, Stephan Vogel, and Aishah Al Daher. 2017. Interpreting Strategies Annotation in the WAW Corpus. In Proceedings of the Workshop Human-Informed Translation and Interpreting Technology, pages 36–43, Varna, Bulgaria. Association for Computational Linguistics, Shoumen, Bulgaria.