Sentiment analysis by deep learning approaches
P. Sreevidya, O.V. Ramana Murthy, S. Veni
Abstract
We propose a model for carrying out deep learning based multimodal sentiment analysis. The MOUD dataset is taken for experimentation purposes. We developed two parallel text based and audio basedmodels and further, fused these heterogeneous feature maps taken from intermediate layers to complete thearchitecture. Performance measures–Accuracy, precision, recall and F1-score–are observed to outperformthe existing models.
Topics & Concepts
Computer scienceSentiment analysisArtificial intelligenceRecallDeep learningFeature (linguistics)Precision and recallNatural language processingMachine learningSpeech recognitionLinguisticsPhilosophySentiment Analysis and Opinion MiningAdvanced Text Analysis TechniquesTopic Modeling