| Model Compression Applied to Small-Footprint Keyword Spotting. G Tucker, M Wu, M Sun, S Panchapagesan, G Fu, S Vitaladevuni INTERSPEECH, 1878-1882, 2016 | 95 | 2016 |
| MONOPHONE-BASED BACKGROUND MODELING FOR TWO-STAGE ON-DEVICE WAKE WORD DETECTION M Wu, S Panchapagesan, M Sun, J Gu, R Thomas, SNP Vitaladevuni, ... | 82 | 2018 |
| Improving noise robustness of automatic speech recognition via parallel data and teacher-student learning L Mošner, M Wu, A Raju, SHK Parthasarathi, K Kumatani, S Sundaram, ... ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 54 | 2019 |
| Pronunciation and silence probability modeling for ASR G Chen, H Xu, M Wu, D Povey, S Khudanpur Sixteenth Annual Conference of the International Speech Communication …, 2015 | 54 | 2015 |
| Direct modeling of raw audio with dnns for wake word detection K Kumatani, S Panchapagesan, M Wu, M Kim, N Strom, G Tiwari, ... 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2017 | 51 | 2017 |
| Time-delayed bottleneck highway networks using a dft feature for keyword spotting J Guo, K Kumatani, M Sun, M Wu, A Raju, N Ström, A Mandal 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 39 | 2018 |
| Frequency domain multi-channel acoustic modeling for distant speech recognition W Minhua, K Kumatani, S Sundaram, N Ström, B Hoffmeister ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 37 | 2019 |
| Wav2vec-C: A Self-supervised Model for Speech Representation Learning S Sadhu, D He, CW Huang, SH Mallidi, M Wu, A Rastrow, A Stolcke, ... arXiv preprint arXiv:2103.08393, 2021 | 28 | 2021 |
| Multi-geometry spatial acoustic modeling for distant speech recognition K Kumatani, W Minhua, S Sundaram, N Ström, B Hoffmeister ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 18 | 2019 |
| An empirical study of cross-lingual transfer learning techniques for small-footprint keyword spotting M Sun, A Schwarz, M Wu, N Strom, S Matsoukas, S Vitaladevuni 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 12 | 2017 |
| Listen with Intent: Improving Speech Recognition with Audio-to-Intent Front-End SN Ray, M Wu, A Raju, P Ghahremani, R Bilgi, M Rao, H Arsikere, ... arXiv preprint arXiv:2105.07071, 2021 | 9 | 2021 |
| Deep multi-channel acoustic modeling A Mandal, K Kumatani, N Strom, M Wu, S Sundaram, B Hoffmeister, ... US Patent 10,726,830, 2020 | 7 | 2020 |
| Deep multi-channel acoustic modeling A Mandal, K Kumatani, N Strom, M Wu, S Sundaram, B Hoffmeister, ... US Patent App. 16/932,049, 2020 | 6 | 2020 |
| Monophone-based background modeling for wakeword detection M Wu, S Panchapagesan, M Sun, SNP Vitaladevuni, B Hoffmeister, ... US Patent 10,964,315, 2021 | 4 | 2021 |
| Robust Multi-Channel Speech Recognition Using Frequency Aligned Network T Park, K Kumatani, M Wu, S Sundaram ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 4 | 2020 |
| Fully Learnable Front-End for Multi-Channel Acoustic Modeling Using Semi-Supervised Learning S Wager, A Khare, M Wu, K Kumatani, S Sundaram ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 2 | 2020 |
| Multi-channel Acoustic Modeling using Mixed Bitrate OPUS Compression A Khare, S Sundaram, M Wu arXiv preprint arXiv:2002.00122, 2020 | 2 | 2020 |
| Attention-based Neural Beamforming Layers for Multi-channel Speech Recognition B Pulugundla, Y Gao, B King, G Keskin, H Mallidi, M Wu, J Droppo, ... arXiv preprint arXiv:2105.05920, 2021 | 1 | 2021 |
| Enhanced Non-linear Features for On-line Handwriting Recognition Using Deep Learning Q Zhang, M Wu, Z Luo, Y Chen International Conference on Neural Information Processing 8834, 358-365, 2014 | 1 | 2014 |
| Do You Listen with One or Two Microphones? A Unified ASR Model for Single and Multi-Channel Audio G Keskin, M Wu, B King, H Mallidi, Y Gao, A Rastrow, R Maas arXiv preprint arXiv:2106.02750, 2021 | | 2021 |
