Cross-Lingual Emotion Classification with Auxiliary and Attention Neural Networks

摘要：

　　In the literature,various supervised learning approaches have been adopted to address the task of emotion classification.However,the performance of these approaches greatly suffers when the size of the labeled data is limited.In this paper,we tackle this challenge from a cross-lingual sensoria where the labeled data in a resource-rich language(i.e.,English in this study)is employed to improve the emotion classification performance in a resource-poor language(i.e.,Chinese in this study).Specifically,we first use machine translation services to eliminate the language gap between Chinese and English data and then propose a joint learning framework to leverage both Chinese and English data,which develops auxiliary representations from several auxiliary emotion classification tasks.Furthermore,in our joint learning approach,we introduce an attention mechanism to capture informative words.Empirical studies demonstrate the effectiveness of the proposed approach to emotion classification.

关键词： Sentiment analysis Emotion classification Attention mechanism

作者: Lu Zhang Liangqing Wu Shoushan Li Zhongqing Wang Guodong Zhou

作者单位: Natural Language Processing Lab,School of Computer Science and Technology,Soochow University,Suzhou,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 429-441

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）