CMU-MOSI、CMU-MOSEI、CMU-MOSEI-OOD

1.The CMU-MOSI dataset is a multimodal dataset created by Carnegie Mellon University for sentiment analysis. Contains 2199 YouTube monologue video clips, covering movie reviews, speeches, and other scenes, with each clip labeled with an emotional rating of [-3, 3]. 2.The CMU-MOSEI dataset is an extended version of the CMU-MOSI dataset. It contains 3228 videos from 1000 speakers, totaling 22856 sentences. 3.The CMU-MOSEI-OOD dataset is constructed using the adaptive simulated annealing algorithm of the CMU-MOSEI dataset, which iteratively adjusts the test distribution to achieve significant differences in word emotion correlation with the training set. This dataset contains two configurations: OOD distribution for second level classification scenarios (labeled CMU-MOSEI *) and OOD distribution for seventh level classification scenarios (labeled CMU-MOSEI * *), corresponding to these two different granularity data partitions. The data annotation is consistent with CMU-MOSEI.