M-SENA: An Integrated Platform for Multimodal Sentiment Analysis

TL;DR

M-SENA is an open-source, modular platform designed to advance multimodal sentiment analysis research by providing comprehensive tools, benchmarks, and visualization features for data management, model training, and analysis.

Contribution

It introduces a fully modular, open-source platform with reliable benchmarks and visualization tools specifically for multimodal sentiment analysis research.

Findings

Baseline results for various modality features are reported.

The platform enables visualization of intermediate representations.

Evaluation tools demonstrate model generalization and robustness.

Abstract

M-SENA is an open-sourced platform for Multimodal Sentiment Analysis. It aims to facilitate advanced research by providing flexible toolkits, reliable benchmarks, and intuitive demonstrations. The platform features a fully modular video sentiment analysis framework consisting of data management, feature extraction, model training, and result analysis modules. In this paper, we first illustrate the overall architecture of the M-SENA platform and then introduce features of the core modules. Reliable baseline results of different modality features and MSA benchmarks are also reported. Moreover, we use model evaluation and analysis tools provided by M-SENA to present intermediate representation visualization, on-the-fly instance test, and generalization ability test results. The source code of the platform is publicly available at https://github.com/thuiar/M-SENA.