activity
20182023
most citedPay Less Attention with Lightweight and Dynamic Convolutions

318 citations · 1.3k across the 22 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.CL2021★ 10 cited

Simple and Effective Zero-shot Cross-lingual Phoneme Recognition

Qiantong Xu, Alexei Baevski, Michael Auli

Recent progress in self-training, self-supervised pretraining and unsupervised learning enabled well performing speech recognition systems without any labeled data. However, in man…

cs.CL2021★ 21 cited

Unsupervised Speech Recognition

Alexei Baevski, Wei-Ning Hsu, Alexis Conneau +1

Despite rapid progress in the recent past, current speech recognition systems still require labeled training data which limits this technology to a small fraction of the languages…

cs.CL2021★ 7 cited

Large-Scale Self- and Semi-Supervised Learning for Speech Translation

Changhan Wang, Anne Wu, Juan Pino +3

In this paper, we improve speech translation (ST) through effectively leveraging large quantities of unlabeled speech and text data in different and complementary ways. We explore…

cs.SD2021

Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Training

Wei-Ning Hsu, Anuroop Sriram, Alexei Baevski +8

Self-supervised learning of speech representations has been a very active research area but most work is focused on a single domain such as read audio books for which there exist l…

cs.CL2021

Generative Spoken Language Modeling from Raw Audio

Kushal Lakhotia, Evgeny Kharitonov, Wei-Ning Hsu +8

We introduce Generative Spoken Language Modeling, the task of learning the acoustic and linguistic characteristics of a language from raw audio (no text, no labels), and a set of m…