2023
SEMEVAL
SemEval 2023
WKU_NLP at SemEval-2023 Task 9: Translation Augmented Multilingual Tweet Intimacy Analysis
Abstract
AbstractThis paper describes a system for the SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis. This system consists of a pretrained multilingual masked language model as a text encoder and a neural network as a regression model. Data augmentation based on neural machine translation models is adopted to improve model performance under the low-resource scenario. This system is further improved through the ensemble of multiple models with the best performance in each language. This system ranks 4th in languages unseen in the training data and 16th in languages seen in the training data. The code and data can be found in this link: https://github.com/Cloudy0219/Multilingual.
🌉
Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
🧭
Keyword Pioneer
— multilingual tweet analysis
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Regression
Machine Learning > Application Areas > Data Augmentation
Natural Language Processing > Understanding > Sentiment Analysis
Natural Language Processing > Resources & Methods > Multilingual NLP
Machine Learning > Learning Types > Transfer Learning
Machine Learning > Learning Types > Regression
Machine Learning > Learning Types > Data Augmentation