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Amit Das
Amit Das
Electrical and Computer Engineering, University of Illinois
Verified email at illinois.edu
Title
Cited by
Cited by
Year
Advancing acoustic-to-word CTC model
J Li, G Ye, A Das, R Zhao, Y Gong
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
1162018
Advancing connectionist temporal classification with attention modeling
A Das, J Li, R Zhao, Y Gong
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
652018
Ultrasound based gesture recognition
A Das, I Tashev, S Mohammed
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
492017
ASR for under-resourced languages from probabilistic transcription
MA Hasegawa-Johnson, P Jyothi, D McCloy, M Mirbagheri, GM Di Liberto, ...
IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (1), 50-63, 2016
392016
Cross-lingual transfer learning during supervised training in low resource scenarios
A Das, M Hasegawa-Johnson
Sixteenth Annual Conference of the International Speech Communication …, 2015
382015
Advancing Acoustic-to-Word CTC Model with Attention and Mixed-Units
A Das, J Li, G Ye, R Zhao, Y Gong
IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (12 …, 2019
302019
High-Accuracy and Low-Latency Speech Recognition with Two-Head Contextual Layer Trajectory LSTM Model
J Li, R Zhao, E Sun, JHM Wong, A Das, Z Meng, Y Gong
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
232020
Multi-Dialect Speech Recognition in English Using Attention on Ensemble of Experts
A Das, K Kumar, J Wu
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
212021
Automatic Speech Recognition Using Probabilistic Transcriptions in Swahili, Amharic, and Dinka.
A Das, P Jyothi, M Hasegawa-Johnson
INTERSPEECH, 3524-3528, 2016
162016
Multiple Softmax Architecture for Streaming Multilingual End-to-End ASR Systems.
V Joshi, A Das, E Sun, RR Mehta, J Li, Y Gong
Interspeech, 1767-1771, 2021
102021
Ultrasonic based gesture recognition
IJ Tashev, S Zarar, A Das
US Patent 10,528,147, 2020
102020
An Investigation on Training Deep Neural Networks Using Probabilistic Transcriptions.
A Das, M Hasegawa-Johnson
Interspeech, 3858-3862, 2016
102016
Universal Acoustic Modeling Using Neural Mixture Models
A Das, J Li, C Liu, Y Gong
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
82019
Deep Auto-Encoder Based Multi-Task Learning Using Probabilistic Transcriptions.
A Das, M Hasegawa-Johnson, K Veselę
INTERSPEECH, 2073-2077, 2017
82017
Constrained iterative speech enhancement using phonetic classes
A Das, JHL Hansen
IEEE transactions on audio, speech, and language processing 20 (6), 1869-1883, 2012
82012
Phoneme selective speech enhancement using parametric estimators and the mixture maximum model: A unifying approach
A Das, JHL Hansen
IEEE transactions on audio, speech, and language processing 20 (8), 2265-2279, 2012
62012
Speech recognition using connectionist temporal classification
A Das, J Li, R Zhao, Y Gong
US Patent 10,580,432, 2020
52020
Phoneme selective speech enhancement using the generalized parametric spectral subtraction estimator
A Das, JHL Hansen
2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011
42011
Improving DNNs Trained with Non-Native Transcriptions Using Knowledge Distillation and Target Interpolation.
A Das, M Hasegawa-Johnson
Interspeech, 2434-2438, 2018
22018
Broad phoneme class based speech enhancement using mixture maximum model
A Das, JHL Hansen
2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010
22010
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