Exploiting Fine-tuning of Self-supervised Learning Models for Improving Bi-modal Sentiment Analysis and Emotion Recognition.
Wei YangSatoru FukayamaPanikos HeracleousJun OgataPublished in: INTERSPEECH (2022)
Keyphrases
- sentiment analysis
- emotion recognition
- learning models
- fine tuning
- machine learning
- text classification
- sentiment classification
- loss function
- semi supervised learning
- learning algorithm
- machine learning algorithms
- sentence level
- learning tasks
- conditional random fields
- text mining
- natural language processing
- learning problems
- classification models
- supervised learning
- bayesian networks
- neural network
- support vector
- face recognition
- decision trees
- artificial intelligence
- data sets