22 citations · 60 across the 15 of their papers we have counts for
4 papers · 1 filter
Accent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings
Jialu Li, Vimal Manohar, Pooja Chitkara +5
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 commo…
Accented Speech Recognition Inspired by Human Perception
Xiangyun Chu, Elizabeth Combs, Amber Wang +1
While improvements have been made in automatic speech recognition performance over the last several years, machines continue to have significantly lower performance on accented spe…
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition
Wei Zhang, Xiaodong Cui, Ulrich Finkler +6
Modern Automatic Speech Recognition (ASR) systems rely on distributed deep learning to for quick training completion. To enable efficient distributed training, it is imperative tha…
Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition
Khoi-Nguyen C. Mac, Xiaodong Cui, Wei Zhang +1
In automatic speech recognition (ASR), wideband (WB) and narrowband (NB) speech signals with different sampling rates typically use separate acoustic models. Therefore mixed-bandwi…