XLS-R: Large-Scale Cross-Lingual Speech Representation Learning on 128 Languages

Explore XLS-R, a groundbreaking large-scale model for cross-lingual speech representation learning based on wav2vec 2.0, in this informative 27-minute talk by Changhan Wang from Meta AI Research. Delve into the model's impressive capabilities, trained on nearly 500,000 hours of public speech audio across 128 languages. Discover how XLS-R significantly improves state-of-the-art performance in speech translation, recognition, and language identification tasks. Learn about its architecture, data distribution, and evaluation results across various benchmarks. Gain insights into future applications, including multilingual translation and speech classification. Understand the potential impact of XLS-R on advancing speech processing for a wide range of global languages and how the open-source community can contribute to its development.

Introduction
Wave to Back 20
XLSR
Comparison
Data Distribution
Evaluation Results
Future Setting
Multilingual Translation
Multilingual Speech Translation
Speech Classification
Summary
XLSR Models
Additional Resources
Questions