In this paper, we present S4D, a new open-source Python toolkit dedicated to speaker diarization. S4D provides various state-ofthe-art components and the possibility to easily develop end-toend diarization prototype systems. S4D offers a large panel of clustering, segmentation, scoring and visualization algorithms. S4D has been thought to be easily understood, installed, modified and used in order to allow fast transfers of diarization technologies to industry and facilitate development of new approaches. Examples, benchmarks on standard tasks and tutorials are provided in this paper. S4D is an extension of the opensource toolkit for speaker recognition: SIDEKIT.

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RÉSUMÉDans cet article, nous présentons un simulateur dédié à l'évaluation des corrections humaines sur la tâche de Segmentation et Regroupement en Locuteurs (SRL). Nous proposons quatre actions élémentaires afin de corriger une SRL et un automate pour simuler la séquence de corrections. Une mesure est proposée pour évaluer le coût de correction. Le simulateur est évalué en utilisant des émissions françaises d'information tirées du corpus REPERE. ABSTRACT Computer-assisted speaker diarization : how to evaluate human correctionsIn this paper, we present a framework to evaluate the human correction of a speaker diarization. We propose four elementary actions to correct the diarization and an automaton to simulate the correction sequence. A metric is described to evaluate the correction cost. The framework is evaluated using French broadcast news drawn from the REPERE corpus.