no code implementations • 1 May 2024 • Huan-Yi Su, Ke wu, Yu-Hao Huang, Wu-Jun Li
One module is for adapting general-purpose LLMs to financial domain, and the other module is for enhancing the ability of NumLLM to understand financial text with numeric variables.
no code implementations • 10 Apr 2024 • Muer Tie, Julong Wei, Zhengjun Wang, Ke wu, Shansuai Yuan, Kaizhao Zhang, Jie Jia, Jieru Zhao, Zhongxue Gan, Wenchao Ding
Online construction of open-ended language scenes is crucial for robotic applications, where open-vocabulary interactive scene understanding is required.
no code implementations • 29 Mar 2024 • Ke wu, Kaizhao Zhang, Zhiwei Zhang, Shanshuai Yuan, Muer Tie, Julong Wei, Zijun Xu, Jieru Zhao, Zhongxue Gan, Wenchao Ding
However, integrating 3DGS into a street-view dense mapping framework still faces two challenges, including incomplete reconstruction due to the absence of geometric information beyond the LiDAR coverage area and extensive computation for reconstruction in large urban scenes.
no code implementations • 20 Oct 2023 • Arya D. McCarthy, Hao Zhang, Shankar Kumar, Felix Stahlberg, Ke wu
One challenge in speech translation is that plenty of spoken content is long-form, but short units are necessary for obtaining high-quality translations.
no code implementations • 31 Jul 2023 • Hao Lin, Ke wu, Jie Li, Jun Li, Wu-Jun Li
To the best of our knowledge, UniAP is the first parallel method that can jointly optimize the two categories of parallel strategies to find an optimal solution.
no code implementations • 14 Jun 2023 • Ben You, Ke wu
Time-periodic form or expression is a ubiquitous natural and man-made phenomenon observable in all the scientific and engineering disciplines.
1 code implementation • 25 Apr 2023 • Ke wu, Ehsan Variani, Tom Bagby, Michael Riley
We introduce LAST, a LAttice-based Speech Transducer library in JAX.
no code implementations • 15 Jan 2023 • Ben Hoar, Roshini Ramachandran, Marc Levis, Erin Sparck, Ke wu, Chong Liu
Often, student opinions are gathered with a general comment section that solicits their feelings towards their courses without polling specifics about course contents.
no code implementations • 22 Dec 2022 • Ehsan Variani, Ke wu, David Rybach, Cyril Allauzen, Michael Riley
Existing training criteria in automatic speech recognition(ASR) permit the model to freely explore more than one time alignments between the feature and label sequences.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
1 code implementation • 26 May 2022 • Ehsan Variani, Ke wu, Michael Riley, David Rybach, Matt Shannon, Cyril Allauzen
We introduce the Globally Normalized Autoregressive Transducer (GNAT) for addressing the label bias problem in streaming speech recognition.
no code implementations • 1 Feb 2022 • Jae Hun Ro, Felix Stahlberg, Ke wu, Shankar Kumar
Text normalization, or the process of transforming text into a consistent, canonical form, is crucial for speech applications such as text-to-speech synthesis (TTS).
1 code implementation • 4 Aug 2021 • Jae Hun Ro, Ananda Theertha Suresh, Ke wu
Federated learning is a machine learning technique that enables training across decentralized data.
no code implementations • 19 Jul 2020 • Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke wu
We present a theoretical and algorithmic study of the multiple-source domain adaptation problem in the common scenario where the learner has access only to a limited amount of labeled target data, but where the learner has at disposal a large amount of labeled data from multiple source domains.
3 code implementations • 12 Mar 2020 • Ke Wu, Didier Darcet, Qian Wang, Didier Sornette
Japan and Italy are in serious situations with no short-term end to the outbreak to be expected.
Populations and Evolution Biological Physics Applications
no code implementations • 31 Dec 2019 • Shuo Huang, Ke wu, Xiaolin Meng, Cheng Li
The non-rigid registration between CT data and ultrasonic images of liver can facilitate the diagnosis and treatment, which has been widely studied in recent years.
no code implementations • 21 Sep 2016 • Ke Wu, Kyle Gorman, Richard Sproat
In speech-applications such as text-to-speech (TTS) or automatic speech recognition (ASR), \emph{text normalization} refers to the task of converting from a \emph{written} representation into a representation of how the text is to be \emph{spoken}.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 19 Feb 2016 • Ke Wu, Malik Magdon-Ismail
Multilayer networks have seen a resurgence under the umbrella of deep learning.