| SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities | 2 | 0.35 | 2022 |
| DUAL: Discrete Spoken Unit Adaptive Learning for Textless Spoken Question Answering | 0 | 0.34 | 2022 |
| Unified Speech-Text Pre-training for Speech Translation and Recognition | 0 | 0.34 | 2022 |
| Editorial Editorial of Special Issue on Self-Supervised Learning for Speech and Audio Processing | 0 | 0.34 | 2022 |
| Robust Self-Supervised Audio-Visual Speech Recognition | 0 | 0.34 | 2022 |
| Self-Supervised Speech Representation Learning: A Review | 0 | 0.34 | 2022 |
| Learning Lip-Based Audio-Visual Speaker Embeddings with AV-HuBERT | 0 | 0.34 | 2022 |
| Text-Free Prosody-Aware Generative Spoken Language Modeling | 2 | 0.35 | 2022 |
| Scaling ASR Improves Zero and Few Shot Learning. | 0 | 0.34 | 2022 |
| Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction | 0 | 0.34 | 2022 |
| HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units | 2 | 0.42 | 2021 |
| Speech Resynthesis from Discrete Disentangled Self-Supervised Representations. | 2 | 0.35 | 2021 |
| HUBERT: HOW MUCH CAN A BAD TEACHER BENEFIT ASR PRE-TRAINING? | 1 | 0.36 | 2021 |
| Kaizen: Continuously Improving Teacher Using Exponential Moving Average for Semi-Supervised Speech Recognition | 3 | 0.37 | 2021 |
| CONTRASTIVE SEMI-SUPERVISED LEARNING FOR ASR | 1 | 0.36 | 2021 |
| Unsupervised Cross-Lingual Representation Learning for Speech Recognition. | 5 | 0.41 | 2021 |
| SUPERB - Speech Processing Universal PERformance Benchmark. | 13 | 0.67 | 2021 |
| Transformer-based Acoustic Modeling for Hybrid Speech Recognition | 2 | 0.39 | 2020 |
| wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations | 0 | 0.34 | 2020 |
| BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension | 2 | 0.36 | 2020 |
| Large scale weakly and semi-supervised learning for low-resource video ASR | 0 | 0.34 | 2020 |
| Transformers with convolutional context for ASR. | 1 | 0.35 | 2019 |
| Mechanical Rubbing of Blood Clots Using Helical Robots Under Ultrasound Guidance. | 1 | 0.39 | 2018 |
| Differentiable Greedy Networks. | 0 | 0.34 | 2018 |
| Direct optimization of F-measure for retrieval-based personal question answering. | 0 | 0.34 | 2018 |
| Neuro-Symbolic Program Synthesis. | 0 | 0.34 | 2017 |
| Deep API Programmer: Learning to Program with APIs. | 4 | 0.46 | 2017 |
| RobustFill: Neural Program Learning under Noisy I/O. | 28 | 0.92 | 2017 |
| Do Deep Convolutional Nets Really Need to be Deep and Convolutional? | 3 | 0.36 | 2017 |
| Mean Actor Critic. | 0 | 0.34 | 2017 |
| Sequence Modeling via Segmentations. | 5 | 0.43 | 2017 |
| Memory-augmented Attention Modelling for Videos. | 0 | 0.34 | 2016 |
| MSR System Description - TAC 2016 KBP Cold Start Slof Filling Track. | 0 | 0.34 | 2016 |
| Do Deep Convolutional Nets Really Need to be Deep (Or Even Convolutional)? | 29 | 1.02 | 2016 |
| Analysis of deep neural networks with the extended data Jacobian matrix | 2 | 0.38 | 2016 |
| LSTM time and frequency recurrence for automatic speech recognition | 10 | 0.52 | 2015 |
| Learning Lexical Embeddings With Syntactic And Lexicographic Knowledge | 2 | 0.35 | 2015 |
| Compressing LSTMs into CNNs | 2 | 0.39 | 2015 |
| Deep bi-directional recurrent networks over spectral windows | 8 | 0.55 | 2015 |
| Deep Convolutional Neural Networks for Large-scale Speech Tasks. | 89 | 3.39 | 2015 |
| Convolutional neural networks for speech recognition | 221 | 7.06 | 2014 |
| Deep convolutional neural networks for LVCSR | 64 | 2.92 | 2013 |
| Learning filter banks within a deep neural network framework | 35 | 1.41 | 2013 |
| Speech recognition with deep recurrent neural networks | 454 | 23.81 | 2013 |
| Improvements To Deep Convolutional Neural Networks For Lvcsr | 57 | 3.67 | 2013 |
| Hybrid speech recognition with Deep Bidirectional LSTM. | 72 | 3.05 | 2013 |
| Multiresolution Deep Belief Networks | 0 | 0.34 | 2012 |
| Multiresolution Deep Belief Networks. | 10 | 0.72 | 2012 |
| Acoustic Modeling Using Deep Belief Networks | 237 | 44.11 | 2012 |
| Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups | 2005 | 111.42 | 2012 |
