John H. L. Hansen
Artificial Intelligence · IEEE Transactions on Speech and Audio Processing · 2000–2018
A researcher in the Science corpus: 12 papers; trusts 51 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 81 citations into it; #7,061 of 35,345 by trust here, #12,244 by citations
- Signal Processing — 76 citations into it; #1,069 of 7,572 by trust here, #2,001 by citations
- Speech & Audio — 44 citations into it; #895 of 1,076 by trust here, #869 by citations
- Natural Language Processing — 21 citations into it
- Model Architectures — 12 citations into it
- Cognitive Neuroscience — 9 citations into it
- Computer Vision and Pattern Recognition — 8 citations into it
Whom John H. L. Hansen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Geoffrey E. Hinton
- Yoshua Bengio
- J. Urgen Schmidhuber
- Sepp Hochreiter
- Patrick Kenny
- Yann LeCun
- Abdel-rahman Mohamed
- Alex Krizhevsky
- Diederik P. Kingma
Who trusts John H. L. Hansen overall
- Joon Son Chung
- Zhongxin Bai
- Chandan K. A. Reddy
- Arsha Nagrani
- Moataz M. H. El Ayadi
- Xiao-Lei Zhang
- Jaesung Huh
- Hannes Gamper
- Kunxia Wang
- Dimitrios Ververidis
Papers from John H. L. Hansen's perspective
Ordered by how strongly the researchers John H. L. Hansen trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- High performance digit recognition in real car environments (2002) — 21 citations
- Conversational In-Vehicle Dialog Systems: The past, present, and future (2016) — 53 citations
- Robust Features in Deep-Learning-Based Speech Recognition (2017) — 36 citations
- Babble Noise: Modeling, Analysis, and Applications (2009) — 80 citations
- Advancing Multi-Accented Lstm-CTC Speech Recognition Using a Domain Specific Student-Teacher Learning Paradigm (2018) — 22 citations
- Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis. (2017) — 391 citations
- On Multi-Domain Training and Adaptation of End-to-End RNN Acoustic Models for Distant Speech Recognition (2017) — 22 citations
- Speaker Recognition by Machines and Humans: A tutorial review (2015) — 622 citations
- Eurospeech 2001-Scandinavia Robust Speech Recognition in Noise : An Evaluation using the SPINE Corpus † (2001)
- "CU-move" : analysis & corpus development for interactive in-vehicle speech systems (2001) — 46 citations
- Nonlinear feature based classification of speech under stress (2001) — 455 citations
- A comparative study of traditional and newly proposed features for recognition of speech under stress (2000) — 300 citations