Demusa: Demo for Multimodal Sentiment Analysis

Soyeon Hong, Jeonghoon Kim, Donghoon Lee, Hyunsouk Cho

Abstract: Recently, a lot of Multimodal Sentiment Analysis (MSA) models appeared to understanding opinions in multimedia. To accelerate MSA researches, CMU-MOSI and CMU-MOSEI were released as the open-datasets. However, it is hard to observe the input data elements in detail and analyze the prediction model results with each video clip for qualitative evaluation. For these reasons, this paper suggests DeMuSA, demo for multimodal sentiment analysis to explore raw data instance and compare prediction models by utterance-level.