| Autovc: Zero-shot voice style transfer with only autoencoder loss K Qian, Y Zhang, S Chang, X Yang, M Hasegawa-Johnson International Conference on Machine Learning, 5210-5219, 2019 | 555 | 2019 |
| End-to-end joint learning of natural language understanding and dialogue manager X Yang, YN Chen, D Hakkani-Tür, P Crook, X Li, J Gao, L Deng 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 104 | 2017 |
| Speech Enhancement Using Bayesian Wavenet. K Qian, Y Zhang, S Chang, X Yang, D Florêncio, M Hasegawa-Johnson Interspeech, 2013-2017, 2017 | 102 | 2017 |
| Joint modeling of accents and acoustics for multi-accent speech recognition X Yang, K Audhkhasi, A Rosenberg, S Thomas, B Ramabhadran, ... 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 89 | 2018 |
| Joint language understanding and dialogue management using binary classification based on forward and backward recurrent neural network X Li, PA Crook, L Deng, J Gao, YN Chen, X Yang US Patent 10,268,679, 2019 | 56 | 2019 |
| Convolutional neural network‐based multi‐label classification of PCB defects L Zhang, Y Jin, X Yang, X Li, X Duan, Y Sun, H Liu The Journal of Engineering 2018 (16), 1612-1616, 2018 | 56 | 2018 |
| Deep learning based speech beamforming K Qian, Y Zhang, S Chang, X Yang, D Florencio, M Hasegawa-Johnson 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 50 | 2018 |
| Redat: Accent-invariant representation for end-to-end asr by domain adversarial training with relabeling H Hu, X Yang, Z Raeesy, J Guo, G Keskin, H Arsikere, A Rastrow, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 29 | 2021 |
| Improvement of segmental mispronunciation detection with prior knowledge extracted from large L2 speech corpus D Luo, X Yang, L Wang Twelfth Annual Conference of the International Speech Communication Association, 2011 | 28 | 2011 |
| Sound source localization for mobile robot based on time difference feature and space grid matching X Li, H Liu, X Yang 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011 | 23 | 2011 |
| Machine learning approaches to improving pronunciation error detection on an imbalanced corpus X Yang, A Loukina, K Evanini IEEE Spoken Language Technology Workshop, South Lake Tahoe, USA, 300-305, 2014 | 22 | 2014 |
| Acoustic landmarks contain more information about the phone string than other frames for automatic speech recognition with deep neural network acoustic model D He, BP Lim, X Yang, M Hasegawa-Johnson, D Chen The Journal of the Acoustical Society of America 143 (6), 3207-3219, 2018 | 15 | 2018 |
| When CTC training meets acoustic landmarks D He, X Yang, BP Lim, Y Liang, M Hasegawa-Johnson, D Chen ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 11 | 2019 |
| A study on landmark detection based on CTC and its application to pronunciation error detection C Niu, J Zhang, X Yang, Y Xie Asia-Pacific Signal and Information Processing Association Annual Summit and …, 2017 | 11 | 2017 |
| Improved ASR for under-resourced languages through multi-task learning with acoustic landmarks D He, BP Lim, X Yang, M Hasegawa-Johnson, D Chen arXiv preprint arXiv:1805.05574, 2018 | 10 | 2018 |
| Landmark-based consonant voicing detection on multilingual corpora X Kong, X Yang, M Hasegawa-Johnson, JY Choi, S Shattuck-Hufnagel arXiv preprint arXiv:1611.03533, 2016 | 10 | 2016 |
| Landmark-Based Pronunciation Error Identification on Chinese Learning X Yang, X Kong, M Hasegawa-Johnson, Y Xie Speech Prosody, 2016, 2016 | 9 | 2016 |
| Selecting frames for automatic speech recognition based on acoustic landmarks D He, BPP Lim, X Yang, M Hasegawa-Johnson, D Chen The Journal of the Acoustical Society of America 141 (5_Supplement), 3468-3468, 2017 | 4 | 2017 |
| Machine learning approaches to improving mispronunciation detection on an imbalanced corpus X Yang University of Illinois at Urbana-Champaign, 2015 | 1 | 2015 |
| NeKo: Toward Post Recognition Generative Correction Large Language Models with Task-Oriented Experts YT Lin, CHH Yang, Z Chen, P Zelasko, X Yang, ZC Chen, KC Puvvada, ... arXiv preprint arXiv:2411.05945, 2024 | | 2024 |
Mark Hasegawa-JohnsonProfessor of Electrical and Computer Engineering, University of IllinoisEmail verificata su illinois.edu