| Transformers are rnns: Fast autoregressive transformers with linear attention A Katharopoulos, A Vyas, N Pappas, F Fleuret International conference on machine learning, 5156-5165, 2020 | 1320 | 2020 |
| Out-of-distribution detection using an ensemble of self supervised leave-out classifiers A Vyas, N Jammalamadaka, X Zhu, D Das, B Kaul, TL Willke European Conference on Computer Vision, 2018 | 269 | 2018 |
| Scaling speech technology to 1,000+ languages V Pratap, A Tjandra, B Shi, P Tomasello, A Babu, S Kundu, A Elkahky, ... Journal of Machine Learning Research 25 (97), 1-52, 2024 | 164 | 2024 |
| Fast transformers with clustered attention A Vyas, A Katharopoulos, F Fleuret Advances in Neural Information Processing Systems 33, 21665-21674, 2020 | 153 | 2020 |
| Voicebox: Text-guided multilingual universal speech generation at scale M Le, A Vyas, B Shi, B Karrer, L Sari, R Moritz, M Williamson, V Manohar, ... Advances in neural information processing systems 36, 2024 | 113 | 2024 |
| Audiobox: Unified audio generation with natural language prompts A Vyas, B Shi, M Le, A Tjandra, YC Wu, B Guo, J Zhang, X Zhang, ... arXiv preprint arXiv:2312.15821, 2023 | 31 | 2023 |
| Analyzing uncertainties in speech recognition using dropout A Vyas, P Dighe, S Tong, H Bourlard ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 28 | 2019 |
| Power efficient compressive sensing for continuous monitoring of ECG and PPG in a wearable system V Natarajan, A Vyas 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), 336-341, 2016 | 24 | 2016 |
| Pkwrap: a pytorch package for lf-mmi training of acoustic models S Madikeri, S Tong, J Zuluaga-Gomez, A Vyas, P Motlicek, H Bourlard arXiv preprint arXiv:2010.03466, 2020 | 21 | 2020 |
| Comparing CTC and LFMMI for out-of-domain adaptation of wav2vec 2.0 acoustic model A Vyas, S Madikeri, H Bourlard Interspeech 2021, 2861--2865, 2021 | 19 | 2021 |
| Commercial block detection in broadcast news videos A Vyas, R Kannao, V Bhargava, P Guha Proceedings of the 2014 Indian Conference on Computer Vision Graphics and …, 2014 | 17 | 2014 |
| On-demand compute reduction with stochastic wav2vec 2.0 A Vyas, WN Hsu, M Auli, A Baevski arXiv preprint arXiv:2204.11934, 2022 | 14 | 2022 |
| Lattice-free MMI adaptation of self-supervised pretrained acoustic models A Vyas, S Madikeri, H Bourlard ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 14 | 2021 |
| Generative pre-training for speech with flow matching AH Liu, M Le, A Vyas, B Shi, A Tjandra, WN Hsu arXiv preprint arXiv:2310.16338, 2023 | 11 | 2023 |
| Compressive sensing for power efficient data aggregation in a wireless sensor network V Natarajan, A Vyas, K Ranganathan, J Joy, H Singh US Patent 10,149,131, 2018 | 11 | 2018 |
| Unbiased Semi-Supervised LF-MMI Training Using Dropout. S Tong, A Vyas, PN Garner, H Bourlard INTERSPEECH, 1576-1580, 2019 | 7 | 2019 |
| Efficient mesh network data gathering V Natarajan, K Ranganathan, JJ Sydir, A Vyas US Patent 10,778,556, 2020 | 6 | 2020 |
| Optical heart rate sensor with reduced power AS Baxi, A Vyas, S Phatak US Patent 10,932,677, 2021 | 4 | 2021 |
| Learning Fine-Grained Controllability on Speech Generation via Efficient Fine-Tuning CM Chien, A Tjandra, A Vyas, M Le, B Shi, WN Hsu arXiv preprint arXiv:2406.06251, 2024 | | 2024 |
| Type of publication: Conference paper Citation: Vyas_INTERSPEECH_2022 Booktitle: Proceedings of Interspeech A Vyas | | 2022 |
Wei-Ning HsuFacebook AI Research (FAIR)在 csail.mit.edu 的电子邮件经过验证
