Online Speaker Diarization with Relation Network

Understand

In this paper, we propose an online speaker diarization system based on Relation Network, named RenoSD.

• Unlike conventional diariztion systems which consist of several independently-optimized modules, RenoSD implements voice-activity-detection (VAD), embedding extraction, and speaker identity association using a single deep neural network.
• The most striking feature of RenoSD is that it adopts a meta-learning strategy for speaker identity association.
• In particular, the relation network learns to learn a deep distance metric in a data-driven way and it can determine through a simple forward pass whether two given segments belong to the same speaker.