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M-SENA: An Integrated Platform for Multimodal Sentiment Analysis

About

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.

Huisheng Mao, Ziqi Yuan, Hua Xu, Wenmeng Yu, Yihe Liu, Kai Gao• 2022

Related benchmarks

TaskDatasetResultRank
Multimodal Sentiment AnalysisCMU-MOSEI (test)--
332
Multimodal Sentiment AnalysisCMU-MOSI (test)--
316
Multimodal Sentiment AnalysisCMU-MOSI--
144
Multimodal Sentiment AnalysisSIMS (test)
Accuracy (2-Class)79.19
78
Multimodal Sentiment ClassificationCH-SIMS 1.0 (test)
Accuracy (2-Class)80.04
11
Multimodal Sentiment RegressionCH-SIMS 1.0 (test)
MAE0.425
11
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Code

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