Roland Maas
Signal Processing · 2013–2021
A researcher in the Science corpus: 5 papers; trusts 7 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 30 citations into it; #4,021 of 7,572 by trust here, #1,709 by citations
- Artificial Intelligence — 26 citations into it; #19,455 of 35,345 by trust here, #12,244 by citations
- Model Architectures — 9 citations into it
- Computational Mechanics — 5 citations into it
Whom Roland Maas trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Roland Maas overall
Papers from Roland Maas's perspective
Ordered by how strongly the researchers Roland Maas trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- The Kaldi Speech Recognition Toolkit
- Deep Neural Networks for Acoustic Modeling in Speech Recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Sequence Transduction with Recurrent Neural Networks
- A Fast Learning Algorithm for Deep Belief Nets
- An investigation of deep neural networks for noise robust speech recognition
Their papers
- The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech (2013) — 431 citations
- Spatial diffuseness features for DNN-based speech recognition in noisy and reverberant environments (2014) — 38 citations
- Attention-based Neural Beamforming Layers for Multi-channel Speech Recognition (2021)
- DiPCo - Dinner Party Corpus (2019) — 72 citations
- A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research (2016) — 398 citations