Pedro J. Moreno Mengibar
Artificial Intelligence · 1994–2023
A researcher in the Science corpus: 22 papers; trusts 172 researchers and is trusted by 62 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 270 citations into it; #5,256 of 35,345 by trust here, #5,834 by citations
- Speech & Audio — 162 citations into it; #453 of 1,076 by trust here, #345 by citations
- Signal Processing — 149 citations into it; #1,043 of 7,572 by trust here, #1,071 by citations
- Natural Language Processing — 86 citations into it; #4,395 of 5,688 by trust here, #3,754 by citations
- Computer Vision and Pattern Recognition — 48 citations into it; #18,681 of 21,575 by trust here, #12,419 by citations
- Representation & Self-Supervised Learning — 41 citations into it
- Model Architectures — 38 citations into it
- Optimization & Training — 19 citations into it
Whom Pedro J. Moreno Mengibar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- J. Urgen Schmidhuber
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Sepp Hochreiter
- Oriol Vinyals
Who trusts Pedro J. Moreno Mengibar overall
- Fernando Perez-Cruz
- Kishore Prahallad
- Kristen Grauman
- Krikamol Muandet
- Bernard Haasdonk
- Hank Liao
- Yoshua Bengio
- Shaohua Kevin Zhou
- Junier B. Oliva
- Barbara Hammer
Papers from Pedro J. Moreno Mengibar's perspective
Ordered by how strongly the researchers Pedro J. Moreno Mengibar trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- 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
- 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)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Supervised Learning of Semantic Classes for Image Annotation and Retrieval (2007) — 999 citations
- Multilingual Speech Recognition with a Single End-to-End Model (2017) — 292 citations
- Automatic language identification using long short-term memory recurrent neural networks (2014) — 164 citations
- Topic segmentation with an aspect hidden Markov model (2001) — 204 citations
- A big data approach to acoustic model training corpus selection (2014) — 30 citations
- Semi-Supervision in ASR: Sequential MixMatch and Factorized TTS-Based Augmentation (2021) — 17 citations
- Automatic language identification using deep neural networks (2014) — 265 citations
- Search by voice in Mandarin Chinese (2010) — 20 citations
- Improving Speech Recognition Using Consistent Predictions on Synthesized Speech (2020) — 54 citations
- Injecting Text in Self-Supervised Speech Pretraining (2021) — 39 citations
- Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages (2023) — 396 citations
- Speech Recognition with Augmented Synthesized Speech (2019) — 151 citations
- Frame-by-frame language identification in short utterances using deep neural networks (2015) — 75 citations
- Parrotron: An End-to-End Speech-to-Speech Conversion Model and its Applications to Hearing-Impaired Speech and Speech Separation (2019) — 125 citations
- A factor automaton approach for the forced alignment of long speech recordings (2009) — 50 citations
- Transliteration Based Approaches to Improve Code-Switched Speech Recognition Performance (2018) — 40 citations
- Improved recognition of contact names in voice commands (2015) — 50 citations
- MAESTRO: Matched Speech Text Representations through Modality Matching (2022) — 125 citations
- Tts4pretrain 2.0: Advancing the use of Text and Speech in ASR Pretraining with Consistency and Contrastive Losses (2022) — 28 citations
- Syllable-based acoustic modeling with CTC-SMBR-LSTM (2017) — 31 citations