| Unsupervised learning of disentangled and interpretable representations from sequential data WN Hsu, Y Zhang, J Glass Advances in neural information processing systems, 1878-1889, 2017 | 101 | 2017 |
| Learning Latent Representations for Speech Generation and Transformation WN Hsu, Y Zhang, J Glass INTERSPEECH, 1273-1277, 2017 | 63 | 2017 |
| Unsupervised domain adaptation for robust speech recognition via variational autoencoder-based data augmentation WN Hsu, Y Zhang, J Glass 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 16-23, 2017 | 44 | 2017 |
| Multi-channel speech recognition: LSTMs all the way through H Erdogan, T Hayashi, JR Hershey, T Hori, C Hori, WN Hsu, S Kim, ... CHiME-4 workshop, 1-4, 2016 | 43 | 2016 |
| Active learning by learning WN Hsu, HT Lin Twenty-Ninth AAAI conference on artificial intelligence, 2015 | 37 | 2015 |
| Semi-supervised training for improving data efficiency in end-to-end speech synthesis YA Chung, Y Wang, WN Hsu, Y Zhang, RJ Skerry-Ryan ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 27 | 2019 |
| Hierarchical generative modeling for controllable speech synthesis WN Hsu, Y Zhang, RJ Weiss, H Zen, Y Wu, Y Wang, Y Cao, Y Jia, Z Chen, ... Seventh International Conference on Learning Representations (ICLR), 2019 | 26 | 2019 |
| Lingvo: a modular and scalable framework for sequence-to-sequence modeling J Shen, P Nguyen, Y Wu, Z Chen, MX Chen, Y Jia, A Kannan, T Sainath, ... arXiv preprint arXiv:1902.08295, 2019 | 22 | 2019 |
| SLS at SemEval-2016 Task 3: Neural-based approaches for ranking in community question answering M Mohtarami, Y Belinkov, WN Hsu, Y Zhang, T Lei, K Bar, S Cyphers, ... Proceedings of the 10th International Workshop on Semantic Evaluation …, 2016 | 22 | 2016 |
| A prioritized grid long short-term memory RNN for speech recognition WN Hsu, Y Zhang, J Glass 2016 IEEE Spoken Language Technology Workshop (SLT), 467-473, 2016 | 19 | 2016 |
| Exploiting depth and highway connections in convolutional recurrent deep neural networks for speech recognition WN Hsu, Y Zhang, A Lee, J Glass INTERSPEECH, 2016 | 19 | 2016 |
| Neural attention for learning to rank questions in community question answering S Romeo, G Da San Martino, A Barrón-Cedeno, A Moschitti, Y Belinkov, ... Proceedings of COLING 2016, the 26th International Conference on …, 2016 | 17 | 2016 |
| Extracting domain invariant features by unsupervised learning for robust automatic speech recognition WN Hsu, J Glass 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 15 | 2018 |
| Disentangling correlated speaker and noise for speech synthesis via data augmentation and adversarial factorization WN Hsu, Y Zhang, RJ Weiss, YA Chung, Y Wang, Y Wu, J Glass ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 12 | 2019 |
| An unsupervised autoregressive model for speech representation learning YA Chung, WN Hsu, H Tang, J Glass arXiv preprint arXiv:1904.03240, 2019 | 12 | 2019 |
| Automatic speech recognition of Arabic multi-genre broadcast media M Najafian, WN Hsu, A Ali, J Glass 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2017 | 9 | 2017 |
| Scalable factorized hierarchical variational autoencoder training WN Hsu, J Glass INTERSPEECH, 2018 | 8 | 2018 |
| Disentangling by Partitioning: A Representation Learning Framework for Multimodal Sensory Data WN Hsu, J Glass arXiv preprint arXiv:1805.11264, 2018 | 7 | 2018 |
| Recurrent neural network encoder with attention for community question answering WN Hsu, Y Zhang, J Glass arXiv preprint arXiv:1603.07044, 2016 | 7 | 2016 |
| Unsupervised adaptation with interpretable disentangled representations for distant conversational speech recognition WN Hsu, H Tang, J Glass INTERSPEECH, 2018 | 6 | 2018 |
James GlassMIT Computer Science and Artificial Intelligence LaboratoryПотвърден имейл адрес: mit.edu
