题名 | Insufficient Data Can Also Rock! Learning to Converse Using Smaller Data with Augmentation |
作者 | |
通讯作者 | Yan, Rui |
发表日期 | 2019
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会议录名称 | |
页码 | 6698-6705
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出版地 | 2275 E BAYSHORE RD, STE 160, PALO ALTO, CA 94303 USA
|
出版者 | |
摘要 | Recent successes of open-domain dialogue generation mainly rely on the advances of deep neural networks. The effectiveness of deep neural network models depends on the amount of training data. As it is laboursome and expensive to acquire a huge amount of data in most scenarios, how to effectively utilize existing data is the crux of this issue. In this paper, we use data augmentation techniques to improve the performance of neural dialogue models on the condition of insufficient data. Specifically, we propose a novel generative model to augment existing data, where the conditional variational autoencoder (CVAE) is employed as the generator to output more training data with diversified expressions. To improve the correlation of each augmented training pair, we design a discriminator with adversarial training to supervise the augmentation process. Moreover, we thoroughly investigate various data augmentation schemes for neural dialogue system with generative models, both GAN and CVAE. Experimental results on two open corpora, Weibo and Twitter, demonstrate the superiority of our proposed data augmentation model. |
学校署名 | 其他
|
语种 | 英语
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相关链接 | [来源记录] |
收录类别 | |
资助项目 | Guangdong Natural Science Foundation[2018A030310129]
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WOS研究方向 | Computer Science
; Engineering
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WOS类目 | Computer Science, Artificial Intelligence
; Computer Science, Theory & Methods
; Engineering, Electrical & Electronic
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WOS记录号 | WOS:000486572501029
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EI入藏号 | 20203509102082
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EI主题词 | Speech processing
; Neural network models
; Social networking (online)
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EI分类号 | Ergonomics and Human Factors Engineering:461.4
; Computer Software, Data Handling and Applications:723
; Artificial Intelligence:723.4
; Speech:751.5
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来源库 | Web of Science
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引用统计 |
被引频次[WOS]:20
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成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/42227 |
专题 | 工学院_计算机科学与工程系 |
作者单位 | 1.Peking Univ, Acad Adv Interdisciplinary Studies, Ctr Data Sci, Beijing, Peoples R China 2.Peking Univ, Inst Comp Sci & Technol, Beijing, Peoples R China 3.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Peoples R China |
推荐引用方式 GB/T 7714 |
Li, Juntao,Qiu, Lisong,Tang, Bo,et al. Insufficient Data Can Also Rock! Learning to Converse Using Smaller Data with Augmentation[C]. 2275 E BAYSHORE RD, STE 160, PALO ALTO, CA 94303 USA:ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE,2019:6698-6705.
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