Speaker identification and clustering using convolutional neural networks

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How researchers see this paper

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VoxCeleb: A Large-Scale Speaker Identification Dataset (2017, background): “This has led to a very recent shift from handcrafted features to the domain of deep CNNs which can be applied to higher dimensional inputs [13, 14] and for speaker identification [15].”
Utterance-level Aggregation for Speaker Recognition in the Wild (2019, methodology): “Earlier deep neural network (DNN) based speaker recognition systems have naı̈vely used pooling methods that have been successful for visual recognition tasks, such as average pooling [2, 3, 7, 8] or fully connected layers [9, 10] to condense frame-level information into utterance-level representatio”
Associative Deep Clustering: Training a Classification Network with No Labels (2018, background): “Several other methods with various quality of results exist [3, 27, 40, 2, 33, 15].”
Clustering with Deep Learning: Taxonomy and New Methods (2018, methodology): “In addition to the mentioned methods, multiple others exist (Premachandran and Yuille, 2016; Harchaoui et al., 2017; Zheng et al., 2016; Chen et al., 2017; Lukic et al., 2016; Wang et al., 2016; Chen, 2015; Hu et al., 2017).”