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20182025
most citedVisual Speech Recognition for Multiple Languages in the Wild

158 citations · 646 across the 34 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

eess.AS2023★ 1 cited

TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch

Jeff Hwang, Moto Hira, Caroline Chen +21

TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research and development of audio and speech technologies by providing…

cs.CV2023

SparseVSR: Lightweight and Noise Robust Visual Speech Recognition

Adriana Fernandez-Lopez, Honglie Chen, Pingchuan Ma +3

Recent advances in deep neural networks have achieved unprecedented success in visual speech recognition. However, there remains substantial disparity between current methods and t…

cs.LG2023

Medical records condensation: a roadmap towards healthcare data democratisation

Yujiang Wang, Anshul Thakur, Mingzhi Dong +5

The prevalence of artificial intelligence (AI) has envisioned an era of healthcare democratisation that promises every stakeholder a new and better way of life. However, the advanc…

cs.CV2023★ 3 cited

SynthVSR: Scaling Up Visual Speech Recognition With Synthetic Supervision

Xubo Liu, Egor Lakomkin, Konstantinos Vougioukas +9

Recently reported state-of-the-art results in visual speech recognition (VSR) often rely on increasingly large amounts of video data, while the publicly available transcribed video…

cs.LG2023★ 6 cited

Learning Neural Constitutive Laws From Motion Observations for Generalizable PDE Dynamics

Pingchuan Ma, Peter Yichen Chen, Bolei Deng +4

We propose a hybrid neural network (NN) and PDE approach for learning generalizable PDE dynamics from motion observations. Many NN approaches learn an end-to-end model that implici…

cs.RO2023★ 4 cited

SoftZoo: A Soft Robot Co-design Benchmark For Locomotion In Diverse Environments

Tsun-Hsuan Wang, Pingchuan Ma, Andrew Everett Spielberg +5

While significant research progress has been made in robot learning for control, unique challenges arise when simultaneously co-optimizing morphology. Existing work has typically b…