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This report describes the submission from Technical University of Catalonia(UPC) to the VoxCeleb Speaker Recognition Challenge (VoxSRC-20) at Interspeech2020. The final submission is a combination of three systems. System-1 is anautoencoder based approach which tries to reconstruct similar i-vectors,whereas System-2 and -3 are Convolutional Neural Network (CNN) based siamesearchitectures. The siamese networks have two and three branches, respectively,where each branch is a CNN encoder. The double-branch siamese performs binaryclassification using cross entropy loss during training. Whereas, ourtriple-branch siamese is trained to learn speaker embeddings using tripletloss. We provide results of our systems on VoxCeleb-1 test, VoxSRC-20validation and test sets.

The UPC Speaker Verification System Submitted to VoxCeleb Speaker Recognition Challenge 2020 (VoxSRC-20)