Search Results for author: Yonghao Song

Found 10 papers, 5 papers with code

Decoding Natural Images from EEG for Object Recognition

2 code implementations25 Aug 2023 Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, Xiaorong Gao

This paper presents a self-supervised framework to demonstrate the feasibility of learning image representations from EEG signals, particularly for object recognition.

Contrastive Learning EEG +2

Transformer-based Spatial-Temporal Feature Learning for EEG Decoding

3 code implementations11 Jun 2021 Yonghao Song, Xueyu Jia, Lie Yang, Longhan Xie

As far as we know, it is the first time that a detailed and complete method based on the transformer idea has been proposed in this field.

Brain Computer Interface EEG +1

Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface

no code implementations8 Feb 2021 Yonghao Song, Lie Yang, Xueyu Jia, Longhan Xie

The cross-subject application of EEG-based brain-computer interface (BCI) has always been limited by large individual difference and complex characteristics that are difficult to perceive.

Data Augmentation EEG +3

Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight

no code implementations ACL 2020 Hengyi Cai, Hongshen Chen, Yonghao Song, Cheng Zhang, Xiaofang Zhao, Dawei Yin

In this paper, we propose a data manipulation framework to proactively reshape the data distribution towards reliable samples by augmenting and highlighting effective learning samples as well as reducing the effect of inefficient samples simultaneously.

Dialogue Generation

Adaptive Parameterization for Neural Dialogue Generation

1 code implementation IJCNLP 2019 Hengyi Cai, Hongshen Chen, Cheng Zhang, Yonghao Song, Xiaofang Zhao, Dawei Yin

For each conversation, the model generates parameters of the encoder-decoder by referring to the input context.

Dialogue Generation

KNPTC: Knowledge and Neural Machine Translation Powered Chinese Pinyin Typo Correction

no code implementations2 May 2018 Hengyi Cai, Xingguang Ji, Yonghao Song, Yan Jin, Yang Zhang, Mairgup Mansur, Xiaofang Zhao

In contrast to previous work, KNPTC is able to integrate explicit knowledge into NMT for pinyin typo correction, and is able to learn to correct a variety of typos without the guidance of manually selected constraints or languagespecific features.

Machine Translation NMT +2

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