31 citations · 51 across the 2 of their papers we have counts for
4 papers
Improving Noise Robustness of an End-to-End Neural Model for Automatic Speech Recognition
Jagadeesh Balam, Jocelyn Huang, Vitaly Lavrukhin +3
We present our experiments in training robust to noise an end-to-end automatic speech recognition (ASR) model using intensive data augmentation. We explore the efficacy of fine-tun…
Cross-Language Transfer Learning, Continuous Learning, and Domain Adaptation for End-to-End Automatic Speech Recognition
Jocelyn Huang, Oleksii Kuchaiev, Patrick O'Neill +5
In this paper, we demonstrate the efficacy of transfer learning and continuous learning for various automatic speech recognition (ASR) tasks. We start with a pre-trained English AS…
QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions
Samuel Kriman, Stanislav Beliaev, Boris Ginsburg +6
We propose a new end-to-end neural acoustic model for automatic speech recognition. The model is composed of multiple blocks with residual connections between them. Each block cons…
NeMo: a toolkit for building AI applications using Neural Modules
Oleksii Kuchaiev, Jason Li, Huyen Nguyen +11
NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI applications through re-usability, abstraction, and composition. NeMo is built around neural modules, c…