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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.
Annotation is the labeling of data by human effort. Annotation is critical to modern machine learning, and Bloomberg has developed years of experience of annotation at scale. This report captures a wealth of wisdom for applied annotation projects, co
We present a lightweight annotation tool, the Data AnnotatoR Tool (DART), for the general task of labeling structured data with textual descriptions. The tool is implemented as an interactive application that reduces human efforts in annotating large
In this paper, we introduce textsc{Yedda}, a lightweight but efficient and comprehensive open-source tool for text span annotation. textsc{Yedda} provides a systematic solution for text span annotation, ranging from collaborative user annotation to a
Electrocardiography plays an essential role in diagnosing and screening cardiovascular diseases in daily healthcare. Deep neural networks have shown the potentials to improve the accuracies of arrhythmia detection based on electrocardiograms (ECGs).
In this manuscript, we introduce a semi-automatic scene graph annotation tool for images, the GeneAnnotator. This software allows human annotators to describe the existing relationships between participators in the visual scene in the form of directe