9 citations · 9 across the 4 of their papers we have counts for
5 papers
Applying GPGPU to Recurrent Neural Network Language Model based Fast Network Search in the Real-Time LVCSR
Kyungmin Lee, Chiyoun Park, Ilhwan Kim +2
Recurrent Neural Network Language Models (RNNLMs) have started to be used in various fields of speech recognition due to their outstanding performance. However, the high computatio…
Sequential Routing Framework: Fully Capsule Network-based Speech Recognition
Kyungmin Lee, Hyunwhan Joe, Hyeontaek Lim +4
Capsule networks (CapsNets) have recently gotten attention as a novel neural architecture. This paper presents the sequential routing framework which we believe is the first method…
Attention based on-device streaming speech recognition with large speech corpus
Kwangyoun Kim, Kyungmin Lee, Dhananjaya Gowda +10
In this paper, we present a new on-device automatic speech recognition (ASR) system based on monotonic chunk-wise attention (MoChA) models trained with large (> 10K hours) corpus.…
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…
Accelerating recurrent neural network language model based online speech recognition system
Kyungmin Lee, Chiyoun Park, Namhoon Kim +1
This paper presents methods to accelerate recurrent neural network based language models (RNNLMs) for online speech recognition systems. Firstly, a lossy compression of the past hi…