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20212026
most citeddata2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language

241 citations · 290 across the 15 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.CL2022

Introducing Semantics into Speech Encoders

Derek Xu, Shuyan Dong, Changhan Wang +10

Recent studies find existing self-supervised speech encoders contain primarily acoustic rather than semantic information. As a result, pipelined supervised automatic speech recogni…

cs.CV2022★ 24 cited

Offline Visual Representation Learning for Embodied Navigation

Karmesh Yadav, Ram Ramrakhya, Arjun Majumdar +5

How should we learn visual representations for embodied agents that must see and move? The status quo is tabula rasa in vivo, i.e. learning visual representations from scratch whil…

cs.LG2022

On-demand compute reduction with stochastic wav2vec 2.0

Apoorv Vyas, Wei-Ning Hsu, Michael Auli +1

Squeeze and Efficient Wav2vec (SEW) is a recently proposed architecture that squeezes the input to the transformer encoder for compute efficient pre-training and inference with wav…

cs.CL2022

Unified Speech-Text Pre-training for Speech Translation and Recognition

Yun Tang, Hongyu Gong, Ning Dong +8

We describe a method to jointly pre-train speech and text in an encoder-decoder modeling framework for speech translation and recognition. The proposed method incorporates four sel…

cs.CL2022

Towards End-to-end Unsupervised Speech Recognition

Alexander H. Liu, Wei-Ning Hsu, Michael Auli +1

Unsupervised speech recognition has shown great potential to make Automatic Speech Recognition (ASR) systems accessible to every language. However, existing methods still heavily r…

cs.CL2022★ 6 cited

Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training

Ramon Sanabria, Wei-Ning Hsu, Alexei Baevski +1

Human speech data comprises a rich set of domain factors such as accent, syntactic and semantic variety, or acoustic environment. Previous work explores the effect of domain mismat…

cs.LG2022★ 241 cited

data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language

Alexei Baevski, Wei-Ning Hsu, Qiantong Xu +3

While the general idea of self-supervised learning is identical across modalities, the actual algorithms and objectives differ widely because they were developed with a single moda…