| 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 | 116 | 2018 |
| 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 | 65 | 2018 |
| Ultrasound based gesture recognition A Das, I Tashev, S Mohammed 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 49 | 2017 |
| 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 | 39 | 2016 |
| 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 | 38 | 2015 |
| 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 | 31 | 2019 |
| 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 | 23 | 2020 |
| 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 | 21 | 2021 |
| Automatic Speech Recognition Using Probabilistic Transcriptions in Swahili, Amharic, and Dinka. A Das, P Jyothi, M Hasegawa-Johnson INTERSPEECH, 3524-3528, 2016 | 16 | 2016 |
| 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 | 11 | 2021 |
| Ultrasonic based gesture recognition IJ Tashev, S Zarar, A Das US Patent 10,528,147, 2020 | 10 | 2020 |
| An Investigation on Training Deep Neural Networks Using Probabilistic Transcriptions. A Das, M Hasegawa-Johnson Interspeech, 3858-3862, 2016 | 10 | 2016 |
| 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 | 8 | 2019 |
| Deep Auto-Encoder Based Multi-Task Learning Using Probabilistic Transcriptions. A Das, M Hasegawa-Johnson, K Veselý INTERSPEECH, 2073-2077, 2017 | 8 | 2017 |
| Constrained iterative speech enhancement using phonetic classes A Das, JHL Hansen IEEE transactions on audio, speech, and language processing 20 (6), 1869-1883, 2012 | 8 | 2012 |
| 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 | 6 | 2012 |
| Speech recognition using connectionist temporal classification A Das, J Li, R Zhao, Y Gong US Patent 10,580,432, 2020 | 5 | 2020 |
| 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 | 4 | 2011 |
| Improving DNNs Trained with Non-Native Transcriptions Using Knowledge Distillation and Target Interpolation. A Das, M Hasegawa-Johnson Interspeech, 2434-2438, 2018 | 2 | 2018 |
| Broad phoneme class based speech enhancement using mixture maximum model A Das, JHL Hansen 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 2 | 2010 |
