@inproceedings{titeux-etal-2020-seshat,
title = "{S}eshat: a Tool for Managing and Verifying Annotation Campaigns of Audio Data",
author = "Titeux, Hadrien and
Riad, Rachid and
Cao, Xuan-Nga and
Hamilakis, Nicolas and
Madden, Kris and
Cristia, Alejandrina and
Bachoud-L{\'e}vi, Anne-Catherine and
Dupoux, Emmanuel",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.861/",
pages = "6976--6982",
language = "eng",
ISBN = "979-10-95546-34-4",
abstract = "We introduce Seshat, a new, simple and open-source software to efficiently manage annotations of speech corpora. The Seshat software allows users to easily customise and manage annotations of large audio corpora while ensuring compliance with the formatting and naming conventions of the annotated output files. In addition, it includes procedures for checking the content of annotations following specific rules that can be implemented in personalised parsers. Finally, we propose a double-annotation mode, for which Seshat computes automatically an associated inter-annotator agreement with the gamma measure taking into account the categorisation and segmentation discrepancies."
}
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<abstract>We introduce Seshat, a new, simple and open-source software to efficiently manage annotations of speech corpora. The Seshat software allows users to easily customise and manage annotations of large audio corpora while ensuring compliance with the formatting and naming conventions of the annotated output files. In addition, it includes procedures for checking the content of annotations following specific rules that can be implemented in personalised parsers. Finally, we propose a double-annotation mode, for which Seshat computes automatically an associated inter-annotator agreement with the gamma measure taking into account the categorisation and segmentation discrepancies.</abstract>
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%0 Conference Proceedings
%T Seshat: a Tool for Managing and Verifying Annotation Campaigns of Audio Data
%A Titeux, Hadrien
%A Riad, Rachid
%A Cao, Xuan-Nga
%A Hamilakis, Nicolas
%A Madden, Kris
%A Cristia, Alejandrina
%A Bachoud-Lévi, Anne-Catherine
%A Dupoux, Emmanuel
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G eng
%F titeux-etal-2020-seshat
%X We introduce Seshat, a new, simple and open-source software to efficiently manage annotations of speech corpora. The Seshat software allows users to easily customise and manage annotations of large audio corpora while ensuring compliance with the formatting and naming conventions of the annotated output files. In addition, it includes procedures for checking the content of annotations following specific rules that can be implemented in personalised parsers. Finally, we propose a double-annotation mode, for which Seshat computes automatically an associated inter-annotator agreement with the gamma measure taking into account the categorisation and segmentation discrepancies.
%U https://aclanthology.org/2020.lrec-1.861/
%P 6976-6982
Markdown (Informal)
[Seshat: a Tool for Managing and Verifying Annotation Campaigns of Audio Data](https://aclanthology.org/2020.lrec-1.861/) (Titeux et al., LREC 2020)
ACL
- Hadrien Titeux, Rachid Riad, Xuan-Nga Cao, Nicolas Hamilakis, Kris Madden, Alejandrina Cristia, Anne-Catherine Bachoud-Lévi, and Emmanuel Dupoux. 2020. Seshat: a Tool for Managing and Verifying Annotation Campaigns of Audio Data. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 6976–6982, Marseille, France. European Language Resources Association.