9 citations · 12 across the 3 of their papers we have counts for
3 papers
eess.AS2019★ 1 cited
Improved Multi-Stage Training of Online Attention-based Encoder-Decoder Models
Abhinav Garg, Dhananjaya Gowda, Ankur Kumar +3
In this paper, we propose a refined multi-stage multi-task training strategy to improve the performance of online attention-based encoder-decoder (AED) models. A three-stage traini…
eess.AS2019★ 2 cited
power-law nonlinearity with maximally uniform distribution criterion for improved neural network training in automatic speech recognition
Chanwoo Kim, Mehul Kumar, Kwangyoun Kim +1
In this paper, we describe the Maximum Uniformity of Distribution (MUD) algorithm with the power-law nonlinearity. In this approach, we hypothesize that neural network training wil…
eess.AS2019★ 9 cited
end-to-end training of a large vocabulary end-to-end speech recognition system
Chanwoo Kim, Sungsoo Kim, Kwangyoun Kim +10
In this paper, we present an end-to-end training framework for building state-of-the-art end-to-end speech recognition systems. Our training system utilizes a cluster of Central Pr…