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Ming Tu
Ming Tu
Research Scientist at Bytedance
Verified email at bytedance.com
Title
Cited by
Cited by
Year
Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs
M Tu, G Wang, J Huang, Y Tang, X He, B Zhou
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
1742019
Select, answer and explain: Interpretable multi-hop reading comprehension over multiple documents
M Tu, K Huang, G Wang, J Huang, X He, B Zhou
Proceedings of the AAAI conference on artificial intelligence 34 (05), 9073-9080, 2020
1692020
Accent Identification by Combining Deep Neural Networks and Recurrent Neural Networks Trained on Long and Short Term Features.
Y Jiao, M Tu, V Berisha, JM Liss
Interspeech, 2388-2392, 2016
762016
Simulating dysarthric speech for training data augmentation in clinical speech applications
Y Jiao, M Tu, V Berisha, J Liss
2018 IEEE international conference on acoustics, speech and signal …, 2018
672018
Speaker-invariant affective representation learning via adversarial training
H Li, M Tu, J Huang, S Narayanan, P Georgiou
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
592020
Multiple instance learning based on graph neural networks
M Tu, J Huang, X He, B Zhou
ICML 2019 workshop on Learning and Reasoning with Graph-Structured …, 2019
58*2019
Speech enhancement based on deep neural networks with skip connections
M Tu, X Zhang
2017 IEEE international conference on acoustics, speech and signal …, 2017
532017
Interpretable Objective Assessment of Dysarthric Speech Based on Deep Neural Networks.
M Tu, V Berisha, J Liss
Interspeech, 1849-1853, 2017
522017
Investigating the role of L1 in automatic pronunciation evaluation of L2 speech
M Tu, A Grabek, J Liss, V Berisha
Proc. Interspeech 2018, 1636-1640, 2018
362018
Ranking the parameters of deep neural networks using the fisher information
M Tu, V Berisha, M Woolf, J Seo, Y Cao
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
362016
Convex weighting criteria for speaking rate estimation
Y Jiao, V Berisha, M Tu, J Liss
IEEE/ACM transactions on audio, speech, and language processing 23 (9), 1421 …, 2015
342015
Reducing the model order of deep neural networks using information theory
M Tu, V Berisha, Y Cao, J Seo
2016 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 93-98, 2016
322016
The relationship between perceptual disturbances in dysarthric speech and automatic speech recognition performance
M Tu, A Wisler, V Berisha, JM Liss
The Journal of the Acoustical Society of America 140 (5), EL416-EL422, 2016
312016
I4U submission to NIST SRE 2018: Leveraging from a decade of shared experiences
KA Lee, V Hautamaki, T Kinnunen, H Yamamoto, K Okabe, V Vestman, ...
arXiv preprint arXiv:1904.07386, 2019
232019
Towards adversarial learning of speaker-invariant representation for speech emotion recognition
M Tu, Y Tang, J Huang, X He, B Zhou
arXiv preprint arXiv:1903.09606, 2019
192019
Online speaking rate estimation using recurrent neural networks
Y Jiao, M Tu, V Berisha, J Liss
2016 ieee international conference on acoustics, speech and signal …, 2016
192016
Efficient neural music generation
MWY Lam, Q Tian, T Li, Z Yin, S Feng, M Tu, Y Ji, R Xia, M Ma, X Song, ...
Advances in Neural Information Processing Systems 36, 2024
142024
Objective assessment of pathological speech using distribution regression
M Tu, V Berisha, J Liss
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
132017
A Discriminative Acoustic-Prosodic Approach for Measuring Local Entrainment
MM Willi, SA Borrie, TS Barrett, M Tu, V Berisha
Proc. Interspeech 2018, 581-585, 2018
112018
Articulation constrained learning with application to speech emotion recognition
M Shah, M Tu, V Berisha, C Chakrabarti, A Spanias
EURASIP journal on audio, speech, and music processing 2019, 1-17, 2019
102019
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Articles 1–20