Marc Delcroix
Signal Processing · 2013–2023
A researcher in the Science corpus: 15 papers; trusts 166 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 198 citations into it; #1,098 of 7,572 by trust here, #671 by citations
- Artificial Intelligence — 168 citations into it; #8,518 of 35,345 by trust here, #6,517 by citations
- Speech & Audio — 105 citations into it; #552 of 1,076 by trust here, #462 by citations
- Computational Mechanics — 37 citations into it
- Natural Language Processing — 35 citations into it
- Computer Vision and Pattern Recognition — 34 citations into it
- Model Architectures — 25 citations into it
- Evaluation & Benchmarks — 18 citations into it; #1,930 of 3,147 by trust here, #2,166 by citations
Whom Marc Delcroix trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Dong Yu
- Yoshua Bengio
- John R. Hershey
- Emmanuel Vincent
- Alex Graves
- Yann LeCun
- Jimmy Ba
- Alex Krizhevsky
Who trusts Marc Delcroix overall
- Mirco Ravanelli
- Kateřina Žmolíková
- Shinji Watanabe
- Shota Horiguchi
- Eliya Nachmani
- Naoyuki Kanda
- Yusuke Fujita
- Cassia Valentini-Botinhao
- Keisuke Kinoshita
- Vijayaditya Peddinti
Papers from Marc Delcroix's perspective
Ordered by how strongly the researchers Marc Delcroix trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices (2015) — 250 citations
- The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech (2013) — 431 citations
- New Era for Robust Speech Recognition (2017) — 48 citations
- Improving Transformer-Based End-to-End Speech Recognition with Connectionist Temporal Classification and Language Model Integration (2019) — 231 citations
- Single Channel Target Speaker Extraction and Recognition with Speaker Beam (2018) — 204 citations
- Speaker-Aware Neural Network Based Beamformer for Speaker Extraction in Speech Mixtures (2017) — 112 citations
- SpeakerBeam: Speaker Aware Neural Network for Target Speaker Extraction in Speech Mixtures (2019) — 288 citations
- Advances in integration of end-to-end neural and clustering-based diarization for real conversational speech (2021) — 87 citations
- Neural Target Speech Extraction: An overview (2023) — 166 citations
- Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR (2020) — 46 citations
- Multimodal SpeakerBeam: Single Channel Target Speech Extraction with Audio-Visual Speaker Clues (2019) — 70 citations
- Listening to Each Speaker One by One with Recurrent Selective Hearing Networks (2018) — 82 citations
- A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research (2016) — 398 citations
- Text-informed speech enhancement with deep neural networks (2015) — 32 citations
- LINEAR PREDICTION-BASED DEREVERBERATION WITH ADVANCED SPEECH ENHANCEMENT AND RECOGNITION TECHNOLOGIES FOR THE REVERB CHALLENGE (2014) — 112 citations