Seshat: A tool for managing and verifying annotation campaigns of audio data
Hadrien Titeux, Rachid Riad, Xuan-Nga Cao, Nicolas Hamilakis, Kris Madden, Alejandrina Cristià, Anne‐Catherine Bachoud‐Lévi, Emmanuel Dupoux · arXiv (Cornell University) · 2020
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 $γ$ measure taking into account the categorisation and segmentation discrepancies.