241 citations · 259 across the 7 of their papers we have counts for
7 papers
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…
XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale
Arun Babu, Changhan Wang, Andros Tjandra +10
This paper presents XLS-R, a large-scale model for cross-lingual speech representation learning based on wav2vec 2.0. We train models with up to 2B parameters on nearly half a mill…
Word Order Does Not Matter For Speech Recognition
Vineel Pratap, Qiantong Xu, Tatiana Likhomanenko +2
In this paper, we study training of automatic speech recognition system in a weakly supervised setting where the order of words in transcript labels of the audio training data is n…
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…
Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition
Vimal Manohar, Tatiana Likhomanenko, Qiantong Xu +5
In this paper, we introduce the Kaizen framework that uses a continuously improving teacher to generate pseudo-labels for semi-supervised speech recognition (ASR). The proposed app…
CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings
Tatiana Likhomanenko, Qiantong Xu, Gabriel Synnaeve +2
Without positional information, attention-based Transformer neural networks are permutation-invariant. Absolute or relative positional embeddings are the most popular ways to feed…
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…