399 citations · 444 across the 4 of their papers we have counts for
5 papers
NeuralVDB: High-resolution Sparse Volume Representation using Hierarchical Neural Networks
Doyub Kim, Minjae Lee, Ken Museth
We introduce NeuralVDB, which improves on an existing industry standard for efficient storage of sparse volumetric data, denoted VDB [Museth 2013], by leveraging recent advancement…
Metric Learning for Keyword Spotting
Jaesung Huh, Minjae Lee, Heesoo Heo +2
The goal of this work is to train effective representations for keyword spotting via metric learning. Most existing works address keyword spotting as a closed-set classification pr…
In defence of metric learning for speaker recognition
Joon Son Chung, Jaesung Huh, Seongkyu Mun +7
The objective of this paper is 'open-set' speaker recognition of unseen speakers, where ideal embeddings should be able to condense information into a compact utterance-level repre…
FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networks
Minjae Lee, Kyuyeon Hwang, Jinhwan Park +3
In this paper, a neural network based real-time speech recognition (SR) system is developed using an FPGA for very low-power operation. The implemented system employs two recurrent…
Online Keyword Spotting with a Character-Level Recurrent Neural Network
Kyuyeon Hwang, Minjae Lee, Wonyong Sung
In this paper, we propose a context-aware keyword spotting model employing a character-level recurrent neural network (RNN) for spoken term detection in continuous speech. The RNN…