Andros Tjandra

Accent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings

2021 · arXiv (Cornell University)

Speech recognition models often obtain degraded performance when tested on speech with unseen accents. Domain-adversarial training (DAT) and multi-task learning (MTL) are two common approaches for building accent-robust ASR models. ASR models using accent embeddings …

XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

2022 · Interspeech 2022

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 million hours of publicly available speech audio in …