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This repository contains an implementation of a deep learning architecture designed for unsupervised or self-supervised classification tasks. The architecture consists of two components: a classifier and an aligner.
Discriminately Boosted Clustering (DBC) builds on DEC by using convolutional autoencoder instead of feed forward autoencoder. It uses the same training scheme, reconstruction loss and cluster assignment hardening loss as DEC. DBC achieves good results on image datasets because of its use of convolutional neural network.
Course project for EE698R (2020-21 Sem 2). An X-Vector Based Speaker Diarization System with AutoEncoder based clustering method. Also supports spectral and KMeans clustering method.