End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures

19 Nov 2019Gabriel SynnaeveQiantong XuJacob KahnTatiana LikhomanenkoEdouard GraveVineel PratapAnuroop SriramVitaliy LiptchinskyRonan Collobert

We study pseudo-labeling for the semi-supervised training of ResNet, Time-Depth Separable ConvNets, and Transformers for speech recognition, with either CTC or Seq2Seq loss functions. We perform experiments on the standard LibriSpeech dataset, and leverage additional unlabeled data from LibriVox through pseudo-labeling... (read more)

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