Ensemble of Neural Networks with Sentiment Words Translation for Code-Switching Emotion Detection
Emotion detection in code-switching texts aims to identify the emotion labels of text which contains more than one language.The difficulties of this task include problems in bridging the gap between languages and capturing crucial semantic information for classification.To address these issues,we propose an ensemble model with sentiment words translation to build a powerful system.Our system first constructs an English-Chinese sentiment dictionary to make a connection between two languages.Afterwards,we separately train several models include CNN,RCNN and Attention based LSTM model.Then combine their classification results to improve the performance.The experiment result shows that our method has a good effect and achieves the second place among nineteen systems.
Emotion detection Code-switching Neural networks Sentiment words translation
Tianchi Yue Chen Chen Shaowu Zhang Hongfei Lin Liang Yang
Dalian University of Technology,Dalian 116023,Liaoning,China
国际会议
2018自然语言处理与中文计算国际会议(NLPCC2018)
呼和浩特
英文
411-419
2018-08-26（万方平台首次上网日期，不代表论文的发表时间）