no code implementations • EMNLP (NLP4ConvAI) 2021 • Peiyao Wang, Joyce Fang, Julia Reinspach
Large-scale pretrained transformer models have demonstrated state-of-the-art (SOTA) performance in a variety of NLP tasks.
1 code implementation • 25 May 2024 • Peiyao Wang, Yuewei Lin, Erik Blasch, Jie Wei, Haibin Ling
Although the performance of Temporal Action Segmentation (TAS) has improved in recent years, achieving promising results often comes with a high computational cost due to dense inputs, complex model structures, and resource-intensive post-processing requirements.
Ranked #3 on Action Segmentation on GTEA
no code implementations • 4 Jan 2024 • JunFeng Hou, Peiyao Wang, Jincheng Zhang, Meng Yang, Minwei Feng, Jingcheng Yin
Deploying end-to-end speech recognition models with limited computing resources remains challenging, despite their impressive performance.
no code implementations • 4 Apr 2023 • Peiyao Wang, Haibin Ling
Fully supervised action segmentation works on frame-wise action recognition with dense annotations and often suffers from the over-segmentation issue.
no code implementations • COLING 2022 • Lahari Poddar, Peiyao Wang, Julia Reinspach
In this paper we propose a framework that incorporates augmented versions of a dialogue context into the learning objective.
no code implementations • 3 Feb 2022 • Shuaishuai Ye, Peiyao Wang, Shunfei Chen, Xinhui Hu, Xinkang Xu
Firstly, we investigated a set of front-end methods, including multi-channel weighted predicted error (WPE), beamforming, speech separation, speech enhancement and so on, to process training, validation and test sets.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • NeurIPS 2020 • Peiyao Wang, Weixin Luo, Yanyu Xu, Haojie Li, Shugong Xu, Jianyu Yang, Shenghua Gao
Spatial Description Resolution, as a language-guided localization task, is proposed for target location in a panoramic street view, given corresponding language descriptions.
no code implementations • 31 Jan 2018 • Xiaotong Lu, Weisheng Dong, Peiyao Wang, Guangming Shi, Xuemei Xie
Instead of reconstructing individual blocks, the whole image is reconstructed from the linear convolutional measurements.
no code implementations • 21 Jan 2018 • Weisheng Dong, Peiyao Wang, Wotao Yin, Guangming Shi, Fangfang Wu, Xiaotong Lu
Then, the iterative process is unfolded into a deep neural network, which is composed of multiple denoisers modules interleaved with back-projection (BP) modules that ensure the observation consistencies.