  In this paper, we present the system submission for the VoxCeleb Speaker
Recognition Challenge 2020 (VoxSRC-20) by the DKU-DukeECE team. For track 1, we
explore various kinds of state-of-the-art front-end extractors with different
pooling layers and objective loss functions. For track 3, we employ an
iterative framework for self-supervised speaker representation learning based
on a deep neural network (DNN). For track 4, we investigate the whole system
pipeline for speaker diarization, including voice activity detection (VAD),
uniform segmentation, speaker embedding extraction, and clustering.
