M-SENA: An Integrated Platform for Multimodal Sentiment Analysis
This platform addresses the need for standardized tools and benchmarks in multimodal sentiment analysis research, though it is incremental as it builds on existing methods.
The authors introduced M-SENA, an open-source platform for multimodal sentiment analysis, providing modular tools, benchmarks, and demonstrations to facilitate research, with reported baseline results for various modality features and benchmarks.
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.