| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 1975 | 2024 |
| A machine learning-based method for the large-scale evaluation of the qualities of the urban environment L Liu, EA Silva, C Wu, H Wang Computers, environment and urban systems 65, 113-125, 2017 | 276 | 2017 |
| Emformer: Efficient memory transformer based acoustic model for low latency streaming speech recognition Y Shi, Y Wang, C Wu, CF Yeh, J Chan, F Zhang, D Le, M Seltzer ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 185 | 2021 |
| Prompting large language models with speech recognition abilities Y Fathullah, C Wu, E Lakomkin, J Jia, Y Shangguan, K Li, J Guo, W Xiong, ... ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 108 | 2024 |
| The llama 3 herd of models, 2024 A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... URL https://arxiv. org/abs/2407.21783 2407, 21783, 0 | 91 | |
| Multi-basis adaptive neural network for rapid adaptation in speech recognition C Wu, MJF Gales 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 82 | 2015 |
| Streaming transformer-based acoustic models using self-attention with augmented memory C Wu, Y Wang, Y Shi, CF Yeh, F Zhang arXiv preprint arXiv:2005.08042, 2020 | 74 | 2020 |
| Combining factorization model and additive forest for collaborative followee recommendation T Chen, L Tang, Q Liu, D Yang, S Xie, X Cao, C Wu, E Yao, Z Liu, Z Jiang, ... KDD CUP, 2012 | 60 | 2012 |
| Improving interpretability and regularization in deep learning C Wu, MJF Gales, A Ragni, P Karanasou, KC Sim IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (2), 256-265, 2017 | 52 | 2017 |
| Stimulated deep neural network for speech recognition C Wu, P Karanasou, MJF Gales, KC Sim Proc. Interspeech, 400-404, 2016 | 44 | 2016 |
| The llama 3 herd of models A Grattafiori, A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, ... arXiv e-prints, arXiv: 2407.21783, 2024 | 36 | 2024 |
| Weak-attention suppression for transformer based speech recognition Y Shi, Y Wang, C Wu, C Fuegen, F Zhang, D Le, CF Yeh, ML Seltzer arXiv preprint arXiv:2005.09137, 2020 | 31 | 2020 |
| AudioChatLlama: Towards General-Purpose Speech Abilities for LLMs Y Fathullah, C Wu, E Lakomkin, K Li, J Jia, Y Shangguan, J Mahadeokar, ... Proceedings of the 2024 Conference of the North American Chapter of the …, 2024 | 29* | 2024 |
| Dissecting user-perceived latency of on-device E2E speech recognition Y Shangguan, R Prabhavalkar, H Su, J Mahadeokar, Y Shi, J Zhou, C Wu, ... arXiv preprint arXiv:2104.02207, 2021 | 29 | 2021 |
| Transformer in action: a comparative study of transformer-based acoustic models for large scale speech recognition applications Y Wang, Y Shi, F Zhang, C Wu, J Chan, CF Yeh, A Xiao ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 28 | 2021 |
| End-to-end speech recognition contextualization with large language models E Lakomkin, C Wu, Y Fathullah, O Kalinli, ML Seltzer, C Fuegen ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 18 | 2024 |
| A machine learning method for the large-scale evaluation of urban visual environment L Liu, H Wang, C Wu arXiv preprint arXiv:1608.03396, 2016 | 18 | 2016 |
| Chinese coreference resolution via ordered filtering X Zhang, C Wu, H Zhao Joint Conference on EMNLP and CoNLL-Shared Task, 95-99, 2012 | 18 | 2012 |
| Streaming transformer transducer based speech recognition using non-causal convolution Y Shi, C Wu, D Wang, A Xiao, J Mahadeokar, X Zhang, C Liu, K Li, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 17 | 2022 |
| Dynamic encoder transducer: A flexible solution for trading off accuracy for latency Y Shi, V Nagaraja, C Wu, J Mahadeokar, D Le, R Prabhavalkar, A Xiao, ... arXiv preprint arXiv:2104.02176, 2021 | 16 | 2021 |
Mark GalesCambridge University確認したメール アドレス: eng.cam.ac.uk
