activity
20182021
most citedSelf-supervised Pretraining of Visual Features in the Wild

139 citations · 139 across the 2 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2020

Beyond English-Centric Multilingual Machine Translation

Angela Fan, Shruti Bhosale, Holger Schwenk +14

Existing work in translation demonstrated the potential of massively multilingual machine translation by training a single model able to translate between any pair of languages. Ho…

cs.CL2020

Scaling Up Online Speech Recognition Using ConvNets

Vineel Pratap, Qiantong Xu, Jacob Kahn +6

We design an online end-to-end speech recognition system based on Time-Depth Separable (TDS) convolutions and Connectionist Temporal Classification (CTC). We improve the core TDS a…

cs.CL2019

Libri-Light: A Benchmark for ASR with Limited or No Supervision

Jacob Kahn, Morgane Rivière, Weiyi Zheng +12

We introduce a new collection of spoken English audio suitable for training speech recognition systems under limited or no supervision. It is derived from open-source audio books f…

cs.CL2019

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

Gabriel Synnaeve, Qiantong Xu, Jacob Kahn +6

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 functio…

cs.CL2018

wav2letter++: The Fastest Open-source Speech Recognition System

Vineel Pratap, Awni Hannun, Qiantong Xu +5

This paper introduces wav2letter++, the fastest open-source deep learning speech recognition framework. wav2letter++ is written entirely in C++, and uses the ArrayFire tensor libra…

cs.CL2018

Fully Convolutional Speech Recognition

Neil Zeghidour, Qiantong Xu, Vitaliy Liptchinsky +3

Current state-of-the-art speech recognition systems build on recurrent neural networks for acoustic and/or language modeling, and rely on feature extraction pipelines to extract me…