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OVERLAP-AWARE LOW-LATENCY ONLINE SPEAKER DIARIZATION BASED ON END-TO-END LOCAL SEGMENTATION

Juan Manuel Coria 1 Hervé Bredin Sahar Ghannay 1 Sophie Rosset 1
1 ILES - Information, Langue Ecrite et Signée
LISN - Laboratoire Interdisciplinaire des Sciences du Numérique, STL - Sciences et Technologies des Langues
Abstract : We propose to address online speaker diarization as a combination of incremental clustering and local diarization applied to a rolling buffer updated every 500ms. Every single step of the proposed pipeline is designed to take full advantage of the strong ability of a recently proposed end-to-end overlapaware segmentation to detect and separate overlapping speakers. In particular, we propose a modified version of the statistics pooling layer (initially introduced in the x-vector architecture) to give less weight to frames where the segmentation model predicts simultaneous speakers. Furthermore, we derive cannot-link constraints from the initial segmentation step to prevent two local speakers from being wrongfully merged during the incremental clustering step. Finally, we show how the latency of the proposed approach can be adjusted between 500ms and 5s to match the requirements of a particular use case, and we provide a systematic analysis of the influence of latency on the overall performance (on AMI, DIHARD and VoxConverse).
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https://hal.archives-ouvertes.fr/hal-03375330
Contributor : Juan Manuel Coria Connect in order to contact the contributor
Submitted on : Tuesday, October 12, 2021 - 4:38:17 PM
Last modification on : Tuesday, January 4, 2022 - 6:46:03 AM
Long-term archiving on: : Thursday, January 13, 2022 - 8:08:41 PM

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  • HAL Id : hal-03375330, version 1

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Juan Manuel Coria, Hervé Bredin, Sahar Ghannay, Sophie Rosset. OVERLAP-AWARE LOW-LATENCY ONLINE SPEAKER DIARIZATION BASED ON END-TO-END LOCAL SEGMENTATION. IEEE Automatic Speech Recognition and Unserstanding Workshop, Dec 2021, Cartagena, Colombia. ⟨hal-03375330⟩

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