Chanwoo Kim

Signal Processing · with Stern · 2008–2017

A researcher in the Science corpus: 6 papers; trusts 6 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 32 citations into it; #869 of 7,572 by trust here, #1,055 by citations
• Artificial Intelligence — 24 citations into it; #5,871 of 35,345 by trust here, #8,706 by citations
• Speech & Audio — 17 citations into it; #504 of 1,076 by trust here, #439 by citations
• Natural Language Processing — 6 citations into it; #2,521 of 5,688 by trust here, #4,183 by citations

Whom Chanwoo Kim trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Rainer Martin
2. Hynek Hermansky
3. Nelson Morgan
4. Tara N. Sainath
5. Richard M. Stern
6. Geoffrey E. Hinton
7. Brian Kingsbury
8. Oriol Vinyals
9. Andrew W. Senior
10. Yoshua Bengio

Who trusts Chanwoo Kim overall

1. Dan Hendrycks
2. Thomas G. Dietterich
3. Wei-Ning Hsu
4. Tara N. Sainath
5. Yu Zhang
6. Arun Narayanan
7. Bo Li
8. Rohit Prabhavalkar
9. Heiga Zen
10. Roza Chojnacka

Papers from Chanwoo Kim's perspective

Ordered by how strongly the researchers Chanwoo Kim trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Long Short-Term Memory
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Understanding the difficulty of training deep feedforward neural networks
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Large Scale Distributed Deep Networks
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Dropout: a simple way to prevent neural networks from overfitting

Their papers

• Power-Normalized Cepstral Coefficients (PNCC) for Robust Speech Recognition (2016) — 448 citations
• Generation of Large-Scale Simulated Utterances in Virtual Rooms to Train Deep-Neural Networks for Far-Field Speech Recognition in Google Home (2017) — 247 citations
• Power-Normalized Cepstral Coefficients (PNCC) for robust speech recognition (2012) — 193 citations
• Multichannel Signal Processing With Deep Neural Networks for Automatic Speech Recognition (2017) — 213 citations
• Robust signal-to-noise ratio estimation based on waveform amplitude distribution analysis (2008) — 227 citations
• Delta-spectral cepstral coefficients for robust speech recognition (2011) — 128 citations